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BEGIN:VTIMEZONE
TZID:America/Chicago
TZURL:http://tzurl.org/zoneinfo-outlook/America/Chicago
X-LIC-LOCATION:America/Chicago
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:19700308T020000
RRULE:FREQ=YEARLY;BYMONTH=3;BYDAY=2SU
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TZOFFSETTO:-0600
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DTSTART:19701101T020000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
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END:VTIMEZONE
BEGIN:VEVENT
SEQUENCE:0
DTSTART;VALUE=DATE:20260622
DTEND;VALUE=DATE:20260623
DTSTAMP:20260622T090637Z
SUMMARY:AI+Science Summer School 2026
UID:642593@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Hosted at the John Hancock Center from June 22–June 26\, the goal of the program is to introduce a new generation of diverse\, interdisciplinary graduate students and postdocs to the emerging field of AI+Science. We also hope this program can build community across institutions and spur new research directions focused on AI-enabled scientific discovery across the physical and biological sciences.  The program is organized by the Eric and Wendy Schmidt AI in Science Fellowship program at the University of Chicago and the University of Chicago Data Science Institute. The AI + Science Summer School is co-hosted by the National Institute for Theory and Mathematics in Biology (NITMB) and SkAI Institute at the John Hancock Center in downtown Chicago.\n\nMore Info: https://datascience.uchicago.edu/events/ai-science-summer-school-2026/
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://datascience.uchicago.edu/events/ai-science-summer-school-2026/
CREATED:20260520T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260520T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:1
DTSTART;VALUE=DATE:20260623
DTEND;VALUE=DATE:20260624
DTSTAMP:20260622T090637Z
SUMMARY:AI+Science Summer School 2026
UID:642594@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Hosted at the John Hancock Center from June 22–June 26\, the goal of the program is to introduce a new generation of diverse\, interdisciplinary graduate students and postdocs to the emerging field of AI+Science. We also hope this program can build community across institutions and spur new research directions focused on AI-enabled scientific discovery across the physical and biological sciences.  The program is organized by the Eric and Wendy Schmidt AI in Science Fellowship program at the University of Chicago and the University of Chicago Data Science Institute. The AI + Science Summer School is co-hosted by the National Institute for Theory and Mathematics in Biology (NITMB) and SkAI Institute at the John Hancock Center in downtown Chicago.\n\nMore Info: https://datascience.uchicago.edu/events/ai-science-summer-school-2026/
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://datascience.uchicago.edu/events/ai-science-summer-school-2026/
CREATED:20260520T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260520T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:2
DTSTART;VALUE=DATE:20260624
DTEND;VALUE=DATE:20260625
DTSTAMP:20260622T090637Z
SUMMARY:AI+Science Summer School 2026
UID:642595@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Hosted at the John Hancock Center from June 22–June 26\, the goal of the program is to introduce a new generation of diverse\, interdisciplinary graduate students and postdocs to the emerging field of AI+Science. We also hope this program can build community across institutions and spur new research directions focused on AI-enabled scientific discovery across the physical and biological sciences.  The program is organized by the Eric and Wendy Schmidt AI in Science Fellowship program at the University of Chicago and the University of Chicago Data Science Institute. The AI + Science Summer School is co-hosted by the National Institute for Theory and Mathematics in Biology (NITMB) and SkAI Institute at the John Hancock Center in downtown Chicago.\n\nMore Info: https://datascience.uchicago.edu/events/ai-science-summer-school-2026/
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://datascience.uchicago.edu/events/ai-science-summer-school-2026/
CREATED:20260520T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260520T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:3
DTSTART;VALUE=DATE:20260625
DTEND;VALUE=DATE:20260626
DTSTAMP:20260622T090637Z
SUMMARY:AI+Science Summer School 2026
UID:642596@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Hosted at the John Hancock Center from June 22–June 26\, the goal of the program is to introduce a new generation of diverse\, interdisciplinary graduate students and postdocs to the emerging field of AI+Science. We also hope this program can build community across institutions and spur new research directions focused on AI-enabled scientific discovery across the physical and biological sciences.  The program is organized by the Eric and Wendy Schmidt AI in Science Fellowship program at the University of Chicago and the University of Chicago Data Science Institute. The AI + Science Summer School is co-hosted by the National Institute for Theory and Mathematics in Biology (NITMB) and SkAI Institute at the John Hancock Center in downtown Chicago.\n\nMore Info: https://datascience.uchicago.edu/events/ai-science-summer-school-2026/
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://datascience.uchicago.edu/events/ai-science-summer-school-2026/
CREATED:20260520T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260520T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:4
DTSTART;VALUE=DATE:20260626
DTEND;VALUE=DATE:20260627
DTSTAMP:20260622T090637Z
SUMMARY:AI+Science Summer School 2026
UID:642597@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Hosted at the John Hancock Center from June 22–June 26\, the goal of the program is to introduce a new generation of diverse\, interdisciplinary graduate students and postdocs to the emerging field of AI+Science. We also hope this program can build community across institutions and spur new research directions focused on AI-enabled scientific discovery across the physical and biological sciences.  The program is organized by the Eric and Wendy Schmidt AI in Science Fellowship program at the University of Chicago and the University of Chicago Data Science Institute. The AI + Science Summer School is co-hosted by the National Institute for Theory and Mathematics in Biology (NITMB) and SkAI Institute at the John Hancock Center in downtown Chicago.\n\nMore Info: https://datascience.uchicago.edu/events/ai-science-summer-school-2026/
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://datascience.uchicago.edu/events/ai-science-summer-school-2026/
CREATED:20260520T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260520T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:5
DTSTART;TZID=America/Chicago:20260630T090000
DTEND;TZID=America/Chicago:20260630T170000
DTSTAMP:20260622T090637Z
SUMMARY:Cell State Transitions and Fate (in)decisions
UID:630168@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The modern revolution in single-cell technologies and lineage tracing tools has enabled measurements at unprecedented resolution and scale\, generating large\, high-dimensional datasets that reveal extensive non-genetic variation and "plasticity" driving diverse cellular outcomes. The concepts of "plasticity\," "cell state\," and "fate" have surged in various biological contexts\, from developmental biology to disease progression\, yet often lack clear consensus definitions.​  The concept of "cell states" was first established by Conrad Waddington in 1957 when he described cellular development following an epigenetic landscape shaped by gene expression. Recently\, "cell state" has seen liberal use in various contexts\, often interchangeably with "cell type" and "cell identity\," resulting in confusion and stalled progress towards the proposed creation of “virtual cells” that can bypass the need for or significantly constrain  physical experiments. Moreover\, developing robust connections from cell states to eventual fates remains challenging.  Robust regulatory control of these cell-fate decisions is essential in development\, homeostasis\, and regeneration\, as well as during dynamic responses to changing contexts\, such as immune responses; however\, it gets altered in pathological conditions\, such as cancer and autoimmune disease. Recent advances in collecting spatiotemporal data about cellular decision-making have created an urgent need for new mathematical and computational approaches. Tools from dynamical systems theory\, information theory\, and stochastic processes are now being employed to decode the trajectories that cells traverse during transitions\, but significant quantitative challenges remain that require novel mathematical frameworks.  This workshop aims to bring together theoreticians\, experimentalists\, statisticians\, and computational modelers to formalize a unified framework for understanding plasticity and cell state-fate relationships. We will explore novel classification and continuous paradigms inspired by physical principles governing biological systems\, reframing traditional machine learning challenges through the lens of physical constraints imposed by biomolecular signaling. This integrated approach offers unique advantages where traditional computational methods face limitations: handling extremely limited data\, addressing inherently noisy biological measurements\, and maintaining interpretability within mechanistic models.  Participants will engage with both theoretical foundations and practical implementations\, gaining insights into how biologically informed computational architectures can yield more robust\, efficient\, and interpretable systems for analyzing complex biological data and ultimately predicting cell fate decisions.\n\nRegister: https://www.nitmb.org/cell-state-transitions-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://planitpurple.northwestern.edu/event/630168
CREATED:20250708T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20250708T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:6
DTSTART;TZID=America/Chicago:20260701T090000
DTEND;TZID=America/Chicago:20260701T170000
DTSTAMP:20260622T090637Z
SUMMARY:Cell State Transitions and Fate (in)decisions
UID:630169@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The modern revolution in single-cell technologies and lineage tracing tools has enabled measurements at unprecedented resolution and scale\, generating large\, high-dimensional datasets that reveal extensive non-genetic variation and "plasticity" driving diverse cellular outcomes. The concepts of "plasticity\," "cell state\," and "fate" have surged in various biological contexts\, from developmental biology to disease progression\, yet often lack clear consensus definitions.​  The concept of "cell states" was first established by Conrad Waddington in 1957 when he described cellular development following an epigenetic landscape shaped by gene expression. Recently\, "cell state" has seen liberal use in various contexts\, often interchangeably with "cell type" and "cell identity\," resulting in confusion and stalled progress towards the proposed creation of “virtual cells” that can bypass the need for or significantly constrain  physical experiments. Moreover\, developing robust connections from cell states to eventual fates remains challenging.  Robust regulatory control of these cell-fate decisions is essential in development\, homeostasis\, and regeneration\, as well as during dynamic responses to changing contexts\, such as immune responses; however\, it gets altered in pathological conditions\, such as cancer and autoimmune disease. Recent advances in collecting spatiotemporal data about cellular decision-making have created an urgent need for new mathematical and computational approaches. Tools from dynamical systems theory\, information theory\, and stochastic processes are now being employed to decode the trajectories that cells traverse during transitions\, but significant quantitative challenges remain that require novel mathematical frameworks.  This workshop aims to bring together theoreticians\, experimentalists\, statisticians\, and computational modelers to formalize a unified framework for understanding plasticity and cell state-fate relationships. We will explore novel classification and continuous paradigms inspired by physical principles governing biological systems\, reframing traditional machine learning challenges through the lens of physical constraints imposed by biomolecular signaling. This integrated approach offers unique advantages where traditional computational methods face limitations: handling extremely limited data\, addressing inherently noisy biological measurements\, and maintaining interpretability within mechanistic models.  Participants will engage with both theoretical foundations and practical implementations\, gaining insights into how biologically informed computational architectures can yield more robust\, efficient\, and interpretable systems for analyzing complex biological data and ultimately predicting cell fate decisions.\n\nRegister: https://www.nitmb.org/cell-state-transitions-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://planitpurple.northwestern.edu/event/630169
CREATED:20250708T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20250708T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:7
DTSTART;TZID=America/Chicago:20260702T090000
DTEND;TZID=America/Chicago:20260702T170000
DTSTAMP:20260622T090637Z
SUMMARY:Cell State Transitions and Fate (in)decisions
UID:630170@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The modern revolution in single-cell technologies and lineage tracing tools has enabled measurements at unprecedented resolution and scale\, generating large\, high-dimensional datasets that reveal extensive non-genetic variation and "plasticity" driving diverse cellular outcomes. The concepts of "plasticity\," "cell state\," and "fate" have surged in various biological contexts\, from developmental biology to disease progression\, yet often lack clear consensus definitions.​  The concept of "cell states" was first established by Conrad Waddington in 1957 when he described cellular development following an epigenetic landscape shaped by gene expression. Recently\, "cell state" has seen liberal use in various contexts\, often interchangeably with "cell type" and "cell identity\," resulting in confusion and stalled progress towards the proposed creation of “virtual cells” that can bypass the need for or significantly constrain  physical experiments. Moreover\, developing robust connections from cell states to eventual fates remains challenging.  Robust regulatory control of these cell-fate decisions is essential in development\, homeostasis\, and regeneration\, as well as during dynamic responses to changing contexts\, such as immune responses; however\, it gets altered in pathological conditions\, such as cancer and autoimmune disease. Recent advances in collecting spatiotemporal data about cellular decision-making have created an urgent need for new mathematical and computational approaches. Tools from dynamical systems theory\, information theory\, and stochastic processes are now being employed to decode the trajectories that cells traverse during transitions\, but significant quantitative challenges remain that require novel mathematical frameworks.  This workshop aims to bring together theoreticians\, experimentalists\, statisticians\, and computational modelers to formalize a unified framework for understanding plasticity and cell state-fate relationships. We will explore novel classification and continuous paradigms inspired by physical principles governing biological systems\, reframing traditional machine learning challenges through the lens of physical constraints imposed by biomolecular signaling. This integrated approach offers unique advantages where traditional computational methods face limitations: handling extremely limited data\, addressing inherently noisy biological measurements\, and maintaining interpretability within mechanistic models.  Participants will engage with both theoretical foundations and practical implementations\, gaining insights into how biologically informed computational architectures can yield more robust\, efficient\, and interpretable systems for analyzing complex biological data and ultimately predicting cell fate decisions.\n\nRegister: https://www.nitmb.org/cell-state-transitions-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://planitpurple.northwestern.edu/event/630170
CREATED:20250708T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20250708T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:8
DTSTART;VALUE=DATE:20260810
DTEND;VALUE=DATE:20260811
DTSTAMP:20260622T090637Z
SUMMARY:NITMB MathBio Ideathon
UID:639562@northwestern.edu
TZID:America/Chicago
DESCRIPTION:This workshop will be structured to facilitate focused discussion and creative insight regarding research topics at the interface between biology and mathematics\, theory and computation.   Participants will:  • Introduce their expertise to one another via lightning talks and individual sharing • Contribute their visions concerning unsolved problems facing their respective fields • Organize into teams to address the most promising collaborative approaches  • Summarize research plans they think are most likely to be successful ​  Workshop participation will be limited.   Attendance will be balanced equally between experimental and theoretical approaches and will be distributed equally across different career stages.   Early career participants are especially encouraged to apply.   Teams will have the opportunity to return through NITMB’s Focused Research Award Program to continue their work together. \n\nMore Info: https://www.nitmb.org/nitmb-mathbio-ideathon\n\nRegister: https://www.nitmb.org/nitmb-mathbio-ideathon
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/nitmb-mathbio-ideathon
CREATED:20260223T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260223T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:9
DTSTART;VALUE=DATE:20260811
DTEND;VALUE=DATE:20260812
DTSTAMP:20260622T090637Z
SUMMARY:NITMB MathBio Ideathon
UID:639563@northwestern.edu
TZID:America/Chicago
DESCRIPTION:This workshop will be structured to facilitate focused discussion and creative insight regarding research topics at the interface between biology and mathematics\, theory and computation.   Participants will:  • Introduce their expertise to one another via lightning talks and individual sharing • Contribute their visions concerning unsolved problems facing their respective fields • Organize into teams to address the most promising collaborative approaches  • Summarize research plans they think are most likely to be successful ​  Workshop participation will be limited.   Attendance will be balanced equally between experimental and theoretical approaches and will be distributed equally across different career stages.   Early career participants are especially encouraged to apply.   Teams will have the opportunity to return through NITMB’s Focused Research Award Program to continue their work together. \n\nMore Info: https://www.nitmb.org/nitmb-mathbio-ideathon\n\nRegister: https://www.nitmb.org/nitmb-mathbio-ideathon
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/nitmb-mathbio-ideathon
CREATED:20260223T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260223T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:10
DTSTART;VALUE=DATE:20260812
DTEND;VALUE=DATE:20260813
DTSTAMP:20260622T090637Z
SUMMARY:NITMB MathBio Ideathon
UID:639564@northwestern.edu
TZID:America/Chicago
DESCRIPTION:This workshop will be structured to facilitate focused discussion and creative insight regarding research topics at the interface between biology and mathematics\, theory and computation.   Participants will:  • Introduce their expertise to one another via lightning talks and individual sharing • Contribute their visions concerning unsolved problems facing their respective fields • Organize into teams to address the most promising collaborative approaches  • Summarize research plans they think are most likely to be successful ​  Workshop participation will be limited.   Attendance will be balanced equally between experimental and theoretical approaches and will be distributed equally across different career stages.   Early career participants are especially encouraged to apply.   Teams will have the opportunity to return through NITMB’s Focused Research Award Program to continue their work together. \n\nMore Info: https://www.nitmb.org/nitmb-mathbio-ideathon\n\nRegister: https://www.nitmb.org/nitmb-mathbio-ideathon
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/nitmb-mathbio-ideathon
CREATED:20260223T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260223T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:11
DTSTART;VALUE=DATE:20260824
DTEND;VALUE=DATE:20260825
DTSTAMP:20260622T090637Z
SUMMARY:Spin Glass Theory and High-Dimensional Landscapes in Biology
UID:636842@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Modern biology is grappling with a new class of problems defined by overwhelming complexity. From understanding evolution to deciphering the neural code\, we are no longer studying linear chains of cause and effect but vast\, high-dimensional systems of interacting components. The central challenge is to navigate the immense “landscape” that are mountainous terrains with countless peaks and valleys. On the other hand\, arising from statistical physics\, the theoretical framework of spin glasses was created precisely to describe systems driven by disorders and frustration - the exact same principles that shape biological complexity. The primary goal of this workshop is to cultivate a shared language and foster concrete collaborations based on this theoretical foundation to produce paradigm-shifting advances. By uniting mathematicians\, physicists\, and biologists\, we aim to seed a new\, interdisciplinary field capable of tackling previously intractable problems in evolution\, neuroscience\, and immunology.\n\nMore Info: https://www.nitmb.org/spin-glass-workshop\n\nRegister: https://www.nitmb.org/spin-glass-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/spin-glass-workshop
CREATED:20251210T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20251210T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:12
DTSTART;VALUE=DATE:20260825
DTEND;VALUE=DATE:20260826
DTSTAMP:20260622T090637Z
SUMMARY:Spin Glass Theory and High-Dimensional Landscapes in Biology
UID:636843@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Modern biology is grappling with a new class of problems defined by overwhelming complexity. From understanding evolution to deciphering the neural code\, we are no longer studying linear chains of cause and effect but vast\, high-dimensional systems of interacting components. The central challenge is to navigate the immense “landscape” that are mountainous terrains with countless peaks and valleys. On the other hand\, arising from statistical physics\, the theoretical framework of spin glasses was created precisely to describe systems driven by disorders and frustration - the exact same principles that shape biological complexity. The primary goal of this workshop is to cultivate a shared language and foster concrete collaborations based on this theoretical foundation to produce paradigm-shifting advances. By uniting mathematicians\, physicists\, and biologists\, we aim to seed a new\, interdisciplinary field capable of tackling previously intractable problems in evolution\, neuroscience\, and immunology.\n\nMore Info: https://www.nitmb.org/spin-glass-workshop\n\nRegister: https://www.nitmb.org/spin-glass-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/spin-glass-workshop
CREATED:20251210T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20251210T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:13
DTSTART;VALUE=DATE:20260826
DTEND;VALUE=DATE:20260827
DTSTAMP:20260622T090637Z
SUMMARY:Spin Glass Theory and High-Dimensional Landscapes in Biology
UID:636844@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Modern biology is grappling with a new class of problems defined by overwhelming complexity. From understanding evolution to deciphering the neural code\, we are no longer studying linear chains of cause and effect but vast\, high-dimensional systems of interacting components. The central challenge is to navigate the immense “landscape” that are mountainous terrains with countless peaks and valleys. On the other hand\, arising from statistical physics\, the theoretical framework of spin glasses was created precisely to describe systems driven by disorders and frustration - the exact same principles that shape biological complexity. The primary goal of this workshop is to cultivate a shared language and foster concrete collaborations based on this theoretical foundation to produce paradigm-shifting advances. By uniting mathematicians\, physicists\, and biologists\, we aim to seed a new\, interdisciplinary field capable of tackling previously intractable problems in evolution\, neuroscience\, and immunology.\n\nMore Info: https://www.nitmb.org/spin-glass-workshop\n\nRegister: https://www.nitmb.org/spin-glass-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/spin-glass-workshop
CREATED:20251210T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20251210T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:14
DTSTART;VALUE=DATE:20260827
DTEND;VALUE=DATE:20260828
DTSTAMP:20260622T090637Z
SUMMARY:Spin Glass Theory and High-Dimensional Landscapes in Biology
UID:636845@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Modern biology is grappling with a new class of problems defined by overwhelming complexity. From understanding evolution to deciphering the neural code\, we are no longer studying linear chains of cause and effect but vast\, high-dimensional systems of interacting components. The central challenge is to navigate the immense “landscape” that are mountainous terrains with countless peaks and valleys. On the other hand\, arising from statistical physics\, the theoretical framework of spin glasses was created precisely to describe systems driven by disorders and frustration - the exact same principles that shape biological complexity. The primary goal of this workshop is to cultivate a shared language and foster concrete collaborations based on this theoretical foundation to produce paradigm-shifting advances. By uniting mathematicians\, physicists\, and biologists\, we aim to seed a new\, interdisciplinary field capable of tackling previously intractable problems in evolution\, neuroscience\, and immunology.\n\nMore Info: https://www.nitmb.org/spin-glass-workshop\n\nRegister: https://www.nitmb.org/spin-glass-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/spin-glass-workshop
CREATED:20251210T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20251210T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:15
DTSTART;VALUE=DATE:20260828
DTEND;VALUE=DATE:20260829
DTSTAMP:20260622T090637Z
SUMMARY:Spin Glass Theory and High-Dimensional Landscapes in Biology
UID:636846@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Modern biology is grappling with a new class of problems defined by overwhelming complexity. From understanding evolution to deciphering the neural code\, we are no longer studying linear chains of cause and effect but vast\, high-dimensional systems of interacting components. The central challenge is to navigate the immense “landscape” that are mountainous terrains with countless peaks and valleys. On the other hand\, arising from statistical physics\, the theoretical framework of spin glasses was created precisely to describe systems driven by disorders and frustration - the exact same principles that shape biological complexity. The primary goal of this workshop is to cultivate a shared language and foster concrete collaborations based on this theoretical foundation to produce paradigm-shifting advances. By uniting mathematicians\, physicists\, and biologists\, we aim to seed a new\, interdisciplinary field capable of tackling previously intractable problems in evolution\, neuroscience\, and immunology.\n\nMore Info: https://www.nitmb.org/spin-glass-workshop\n\nRegister: https://www.nitmb.org/spin-glass-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/spin-glass-workshop
CREATED:20251210T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20251210T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:16
DTSTART;VALUE=DATE:20260914
DTEND;VALUE=DATE:20260915
DTSTAMP:20260622T090637Z
SUMMARY:Biological Function in Space and Time: From Forces and Cues to Emerging Decision-making in Fates\, States\, and Shapes
UID:639567@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Biological systems are physical systems operating in space and time. Understanding how they leverage dynamics and spatial extension to achieve functions\, transforming physical cues into decisions\, is a compelling challenge which requires new mathematical frameworks to identify and characterize emerging patterns in modern high-dimensional data\, to quantify reproducibility\, to describe how the information is encoded and transferred across scales\, and to elucidate decision-making mechanisms.   The goal of this workshop is to bring together experimental biologists\, specialists in data analysis and theorists to identify current challenges\, establish collaborations\, and discuss strategies to advance our understanding of how biological systems maintain and organize function across space and time. Researchers across biological subfields have developed formalisms and concepts adapted to their systems of interest. By breaking the traditional barriers of scale\, we hope this meeting can be a way of identifying universal hallmarks disseminated across fields.\n\nMore Info: https://www.nitmb.org/biological-functionin-space-and-time-workshop\n\nRegister: https://www.nitmb.org/biological-functionin-space-and-time-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/biological-functionin-space-and-time-workshop
CREATED:20260223T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260223T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:17
DTSTART;VALUE=DATE:20260915
DTEND;VALUE=DATE:20260916
DTSTAMP:20260622T090637Z
SUMMARY:Biological Function in Space and Time: From Forces and Cues to Emerging Decision-making in Fates\, States\, and Shapes
UID:639568@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Biological systems are physical systems operating in space and time. Understanding how they leverage dynamics and spatial extension to achieve functions\, transforming physical cues into decisions\, is a compelling challenge which requires new mathematical frameworks to identify and characterize emerging patterns in modern high-dimensional data\, to quantify reproducibility\, to describe how the information is encoded and transferred across scales\, and to elucidate decision-making mechanisms.   The goal of this workshop is to bring together experimental biologists\, specialists in data analysis and theorists to identify current challenges\, establish collaborations\, and discuss strategies to advance our understanding of how biological systems maintain and organize function across space and time. Researchers across biological subfields have developed formalisms and concepts adapted to their systems of interest. By breaking the traditional barriers of scale\, we hope this meeting can be a way of identifying universal hallmarks disseminated across fields.\n\nMore Info: https://www.nitmb.org/biological-functionin-space-and-time-workshop\n\nRegister: https://www.nitmb.org/biological-functionin-space-and-time-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/biological-functionin-space-and-time-workshop
CREATED:20260223T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260223T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:18
DTSTART;VALUE=DATE:20260916
DTEND;VALUE=DATE:20260917
DTSTAMP:20260622T090637Z
SUMMARY:Biological Function in Space and Time: From Forces and Cues to Emerging Decision-making in Fates\, States\, and Shapes
UID:639569@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Biological systems are physical systems operating in space and time. Understanding how they leverage dynamics and spatial extension to achieve functions\, transforming physical cues into decisions\, is a compelling challenge which requires new mathematical frameworks to identify and characterize emerging patterns in modern high-dimensional data\, to quantify reproducibility\, to describe how the information is encoded and transferred across scales\, and to elucidate decision-making mechanisms.   The goal of this workshop is to bring together experimental biologists\, specialists in data analysis and theorists to identify current challenges\, establish collaborations\, and discuss strategies to advance our understanding of how biological systems maintain and organize function across space and time. Researchers across biological subfields have developed formalisms and concepts adapted to their systems of interest. By breaking the traditional barriers of scale\, we hope this meeting can be a way of identifying universal hallmarks disseminated across fields.\n\nMore Info: https://www.nitmb.org/biological-functionin-space-and-time-workshop\n\nRegister: https://www.nitmb.org/biological-functionin-space-and-time-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/biological-functionin-space-and-time-workshop
CREATED:20260223T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260223T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:19
DTSTART;VALUE=DATE:20260917
DTEND;VALUE=DATE:20260918
DTSTAMP:20260622T090637Z
SUMMARY:Biological Function in Space and Time: From Forces and Cues to Emerging Decision-making in Fates\, States\, and Shapes
UID:639570@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Biological systems are physical systems operating in space and time. Understanding how they leverage dynamics and spatial extension to achieve functions\, transforming physical cues into decisions\, is a compelling challenge which requires new mathematical frameworks to identify and characterize emerging patterns in modern high-dimensional data\, to quantify reproducibility\, to describe how the information is encoded and transferred across scales\, and to elucidate decision-making mechanisms.   The goal of this workshop is to bring together experimental biologists\, specialists in data analysis and theorists to identify current challenges\, establish collaborations\, and discuss strategies to advance our understanding of how biological systems maintain and organize function across space and time. Researchers across biological subfields have developed formalisms and concepts adapted to their systems of interest. By breaking the traditional barriers of scale\, we hope this meeting can be a way of identifying universal hallmarks disseminated across fields.\n\nMore Info: https://www.nitmb.org/biological-functionin-space-and-time-workshop\n\nRegister: https://www.nitmb.org/biological-functionin-space-and-time-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/biological-functionin-space-and-time-workshop
CREATED:20260223T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260223T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:20
DTSTART;VALUE=DATE:20260918
DTEND;VALUE=DATE:20260919
DTSTAMP:20260622T090637Z
SUMMARY:Biological Function in Space and Time: From Forces and Cues to Emerging Decision-making in Fates\, States\, and Shapes
UID:639571@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Biological systems are physical systems operating in space and time. Understanding how they leverage dynamics and spatial extension to achieve functions\, transforming physical cues into decisions\, is a compelling challenge which requires new mathematical frameworks to identify and characterize emerging patterns in modern high-dimensional data\, to quantify reproducibility\, to describe how the information is encoded and transferred across scales\, and to elucidate decision-making mechanisms.   The goal of this workshop is to bring together experimental biologists\, specialists in data analysis and theorists to identify current challenges\, establish collaborations\, and discuss strategies to advance our understanding of how biological systems maintain and organize function across space and time. Researchers across biological subfields have developed formalisms and concepts adapted to their systems of interest. By breaking the traditional barriers of scale\, we hope this meeting can be a way of identifying universal hallmarks disseminated across fields.\n\nMore Info: https://www.nitmb.org/biological-functionin-space-and-time-workshop\n\nRegister: https://www.nitmb.org/biological-functionin-space-and-time-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/biological-functionin-space-and-time-workshop
CREATED:20260223T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260223T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:21
DTSTART;TZID=America/Chicago:20260928T083000
DTEND;TZID=America/Chicago:20260928T170000
DTSTAMP:20260622T090637Z
SUMMARY:Data-driven modeling\, simulation and inference for neurobiological problems
UID:637986@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The field of neuroscience is undergoing a transformative era\, driven by the convergence of mathematical\, computational\, and experimental approaches. This workshop explores the intersection between these fields through the lenses of mathematical/computational statistics and numerical analysis.   While the potential impact of these approaches to neurosciences problems is fully recognised\, there is still modest cross-fertilization between disciplines. Moreover\,  bespoke numerical methods must be developed for brain dynamics\, to tackle the nonlocality and the nonlinearity of the underlying evolution equations.  Key themes of the workshop include:  • Integrating mathematical models with experimental data.  • Advanced numerical techniques for neural network simulation.  • Numerical analysis of nonlocal and nonlinear neural evolution equations
.  • Statistical inference in neurobiological systems.  • Uncertainty quantification in neural dynamics.  • Inverse problem methodologies in neuroscience
.  The event is targeted at mathematicians\, statisticians\, computational scientists\, and neuroscience researchers\, and will provide a platform for connecting leading experts working in different disciplines and exploring mathematical innovations in these areas.\n\nMore Info: https://www.nitmb.org/neurobio-problems-workshop\n\nRegister: https://www.nitmb.org/neurobio-problems-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/neurobio-problems-workshop
CREATED:20260109T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260109T060000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:22
DTSTART;TZID=America/Chicago:20260929T083000
DTEND;TZID=America/Chicago:20260929T170000
DTSTAMP:20260622T090637Z
SUMMARY:Data-driven modeling\, simulation and inference for neurobiological problems
UID:637987@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The field of neuroscience is undergoing a transformative era\, driven by the convergence of mathematical\, computational\, and experimental approaches. This workshop explores the intersection between these fields through the lenses of mathematical/computational statistics and numerical analysis.   While the potential impact of these approaches to neurosciences problems is fully recognised\, there is still modest cross-fertilization between disciplines. Moreover\,  bespoke numerical methods must be developed for brain dynamics\, to tackle the nonlocality and the nonlinearity of the underlying evolution equations.  Key themes of the workshop include:  • Integrating mathematical models with experimental data.  • Advanced numerical techniques for neural network simulation.  • Numerical analysis of nonlocal and nonlinear neural evolution equations
.  • Statistical inference in neurobiological systems.  • Uncertainty quantification in neural dynamics.  • Inverse problem methodologies in neuroscience
.  The event is targeted at mathematicians\, statisticians\, computational scientists\, and neuroscience researchers\, and will provide a platform for connecting leading experts working in different disciplines and exploring mathematical innovations in these areas.\n\nMore Info: https://www.nitmb.org/neurobio-problems-workshop\n\nRegister: https://www.nitmb.org/neurobio-problems-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/neurobio-problems-workshop
CREATED:20260109T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260109T060000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:23
DTSTART;TZID=America/Chicago:20260930T083000
DTEND;TZID=America/Chicago:20260930T170000
DTSTAMP:20260622T090637Z
SUMMARY:Data-driven modeling\, simulation and inference for neurobiological problems
UID:637988@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The field of neuroscience is undergoing a transformative era\, driven by the convergence of mathematical\, computational\, and experimental approaches. This workshop explores the intersection between these fields through the lenses of mathematical/computational statistics and numerical analysis.   While the potential impact of these approaches to neurosciences problems is fully recognised\, there is still modest cross-fertilization between disciplines. Moreover\,  bespoke numerical methods must be developed for brain dynamics\, to tackle the nonlocality and the nonlinearity of the underlying evolution equations.  Key themes of the workshop include:  • Integrating mathematical models with experimental data.  • Advanced numerical techniques for neural network simulation.  • Numerical analysis of nonlocal and nonlinear neural evolution equations
.  • Statistical inference in neurobiological systems.  • Uncertainty quantification in neural dynamics.  • Inverse problem methodologies in neuroscience
.  The event is targeted at mathematicians\, statisticians\, computational scientists\, and neuroscience researchers\, and will provide a platform for connecting leading experts working in different disciplines and exploring mathematical innovations in these areas.\n\nMore Info: https://www.nitmb.org/neurobio-problems-workshop\n\nRegister: https://www.nitmb.org/neurobio-problems-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/neurobio-problems-workshop
CREATED:20260109T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260109T060000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:24
DTSTART;TZID=America/Chicago:20261001T083000
DTEND;TZID=America/Chicago:20261001T170000
DTSTAMP:20260622T090637Z
SUMMARY:Data-driven modeling\, simulation and inference for neurobiological problems
UID:637989@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The field of neuroscience is undergoing a transformative era\, driven by the convergence of mathematical\, computational\, and experimental approaches. This workshop explores the intersection between these fields through the lenses of mathematical/computational statistics and numerical analysis.   While the potential impact of these approaches to neurosciences problems is fully recognised\, there is still modest cross-fertilization between disciplines. Moreover\,  bespoke numerical methods must be developed for brain dynamics\, to tackle the nonlocality and the nonlinearity of the underlying evolution equations.  Key themes of the workshop include:  • Integrating mathematical models with experimental data.  • Advanced numerical techniques for neural network simulation.  • Numerical analysis of nonlocal and nonlinear neural evolution equations
.  • Statistical inference in neurobiological systems.  • Uncertainty quantification in neural dynamics.  • Inverse problem methodologies in neuroscience
.  The event is targeted at mathematicians\, statisticians\, computational scientists\, and neuroscience researchers\, and will provide a platform for connecting leading experts working in different disciplines and exploring mathematical innovations in these areas.\n\nMore Info: https://www.nitmb.org/neurobio-problems-workshop\n\nRegister: https://www.nitmb.org/neurobio-problems-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/neurobio-problems-workshop
CREATED:20260109T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260109T060000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:25
DTSTART;TZID=America/Chicago:20261002T083000
DTEND;TZID=America/Chicago:20261002T170000
DTSTAMP:20260622T090637Z
SUMMARY:Data-driven modeling\, simulation and inference for neurobiological problems
UID:637990@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The field of neuroscience is undergoing a transformative era\, driven by the convergence of mathematical\, computational\, and experimental approaches. This workshop explores the intersection between these fields through the lenses of mathematical/computational statistics and numerical analysis.   While the potential impact of these approaches to neurosciences problems is fully recognised\, there is still modest cross-fertilization between disciplines. Moreover\,  bespoke numerical methods must be developed for brain dynamics\, to tackle the nonlocality and the nonlinearity of the underlying evolution equations.  Key themes of the workshop include:  • Integrating mathematical models with experimental data.  • Advanced numerical techniques for neural network simulation.  • Numerical analysis of nonlocal and nonlinear neural evolution equations
.  • Statistical inference in neurobiological systems.  • Uncertainty quantification in neural dynamics.  • Inverse problem methodologies in neuroscience
.  The event is targeted at mathematicians\, statisticians\, computational scientists\, and neuroscience researchers\, and will provide a platform for connecting leading experts working in different disciplines and exploring mathematical innovations in these areas.\n\nMore Info: https://www.nitmb.org/neurobio-problems-workshop\n\nRegister: https://www.nitmb.org/neurobio-problems-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/neurobio-problems-workshop
CREATED:20260109T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260109T060000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:26
DTSTART;VALUE=DATE:20261012
DTEND;VALUE=DATE:20261013
DTSTAMP:20260622T090637Z
SUMMARY:NITMB Scientific Focus: Theory and Mathematics in Neuroscience - Dynamics in Neuroscience Workshop
UID:642765@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Recent advances in our ability to record simultaneously from large numbers of neurons has shifted the focus in neuroscience from understanding dynamics at a single cell level to the network level. At the same time\, the rise of modern machine learning has independently generated interest in how computation arises from the coordinated activity of large networks of simple units. This workshop explores how computation emerges from network dynamics\, asking how circuit structure\, network architecture\, and plasticity/learning shape the neural dynamics underlying cognitive functions.  Part of the NITMB Scientific Focus: Theory and Mathematics in Neuroscience\n\nMore Info: https://www.nitmb.org/dynamics-in-neuroscience-workshop\n\nRegister: https://www.nitmb.org/dynamics-in-neuroscience-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/dynamics-in-neuroscience-workshop
CREATED:20260604T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260604T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:27
DTSTART;VALUE=DATE:20261013
DTEND;VALUE=DATE:20261014
DTSTAMP:20260622T090637Z
SUMMARY:NITMB Scientific Focus: Theory and Mathematics in Neuroscience - Dynamics in Neuroscience Workshop
UID:642766@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Recent advances in our ability to record simultaneously from large numbers of neurons has shifted the focus in neuroscience from understanding dynamics at a single cell level to the network level. At the same time\, the rise of modern machine learning has independently generated interest in how computation arises from the coordinated activity of large networks of simple units. This workshop explores how computation emerges from network dynamics\, asking how circuit structure\, network architecture\, and plasticity/learning shape the neural dynamics underlying cognitive functions.  Part of the NITMB Scientific Focus: Theory and Mathematics in Neuroscience\n\nMore Info: https://www.nitmb.org/dynamics-in-neuroscience-workshop\n\nRegister: https://www.nitmb.org/dynamics-in-neuroscience-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/dynamics-in-neuroscience-workshop
CREATED:20260604T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260604T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:28
DTSTART;VALUE=DATE:20261014
DTEND;VALUE=DATE:20261015
DTSTAMP:20260622T090637Z
SUMMARY:NITMB Scientific Focus: Theory and Mathematics in Neuroscience - Dynamics in Neuroscience Workshop
UID:642767@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Recent advances in our ability to record simultaneously from large numbers of neurons has shifted the focus in neuroscience from understanding dynamics at a single cell level to the network level. At the same time\, the rise of modern machine learning has independently generated interest in how computation arises from the coordinated activity of large networks of simple units. This workshop explores how computation emerges from network dynamics\, asking how circuit structure\, network architecture\, and plasticity/learning shape the neural dynamics underlying cognitive functions.  Part of the NITMB Scientific Focus: Theory and Mathematics in Neuroscience\n\nMore Info: https://www.nitmb.org/dynamics-in-neuroscience-workshop\n\nRegister: https://www.nitmb.org/dynamics-in-neuroscience-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/dynamics-in-neuroscience-workshop
CREATED:20260604T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260604T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:29
DTSTART;TZID=America/Chicago:20261019T083000
DTEND;TZID=America/Chicago:20261019T170000
DTSTAMP:20260622T090637Z
SUMMARY:Representing and Learning Morphology and Shape Dynamics from Biological Data
UID:631543@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Advances in high-throughput imaging techniques now generate massive amounts of multiscale image data\, ranging from whole tissues to single cells to protein structures. Beyond static snapshots\, novel imaging methods capture long time-series that provide valuable spatio-temporal information. Analyzing this unprecedented volume of biological data raises a variety of mathematical challenges. Notably\, how can we model biological variation while disentangling biological variation from technical heterogeneity? For example\, how do single cells grow and progress through the cell cycle under diverse stimuli\, or how do proteins and molecular complexes undergo conformational changes? Despite the richness of these data\, methods for spatio-temporal analysis remain limited in computational biology. At the same time\, tools from multiple disciplines—such as deep learning in computer science\, mechanistic models in biophysics\, and dynamical systems theory in mathematics—have been developed to study related problems. In this context\, our proposed workshop will focus on theoretical and computational tools from mathematics and physics that enable rigorous analysis of spatio-temporal biological data\, with the goal of elucidating the temporal dynamics of underlying biological processes.   Intended for a diverse audience of mathematicians\, physicists\, and computational and experimental biologists\, the workshop will feature complimentary sessions on different facets of imaging data\, with a particular focus on dynamics. Our interdisciplinary organizing team will begin with a general overview of shape space\, highlighting both theoretical foundations and state-of-the-art computational tools. We will then present several publicly available datasets on protein and cell shapes from advanced imaging experiments\, and brainstorm methods to uncover the dynamics underlying observed heterogeneity. The ultimate goal of the workshop is to develop a blueprint for new frameworks to study dynamics in shape space and to foster collaborations across mathematics\, computer science\, and biology.\n\nMore Info: https://www.nitmb.org/representing-and-learning-morphology-workshop\n\nRegister: https://www.nitmb.org/representing-and-learning-morphology-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/representing-and-learning-morphology-workshop
CREATED:20250818T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20250818T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:30
DTSTART;TZID=America/Chicago:20261020T083000
DTEND;TZID=America/Chicago:20261020T170000
DTSTAMP:20260622T090637Z
SUMMARY:Representing and Learning Morphology and Shape Dynamics from Biological Data
UID:631544@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Advances in high-throughput imaging techniques now generate massive amounts of multiscale image data\, ranging from whole tissues to single cells to protein structures. Beyond static snapshots\, novel imaging methods capture long time-series that provide valuable spatio-temporal information. Analyzing this unprecedented volume of biological data raises a variety of mathematical challenges. Notably\, how can we model biological variation while disentangling biological variation from technical heterogeneity? For example\, how do single cells grow and progress through the cell cycle under diverse stimuli\, or how do proteins and molecular complexes undergo conformational changes? Despite the richness of these data\, methods for spatio-temporal analysis remain limited in computational biology. At the same time\, tools from multiple disciplines—such as deep learning in computer science\, mechanistic models in biophysics\, and dynamical systems theory in mathematics—have been developed to study related problems. In this context\, our proposed workshop will focus on theoretical and computational tools from mathematics and physics that enable rigorous analysis of spatio-temporal biological data\, with the goal of elucidating the temporal dynamics of underlying biological processes.   Intended for a diverse audience of mathematicians\, physicists\, and computational and experimental biologists\, the workshop will feature complimentary sessions on different facets of imaging data\, with a particular focus on dynamics. Our interdisciplinary organizing team will begin with a general overview of shape space\, highlighting both theoretical foundations and state-of-the-art computational tools. We will then present several publicly available datasets on protein and cell shapes from advanced imaging experiments\, and brainstorm methods to uncover the dynamics underlying observed heterogeneity. The ultimate goal of the workshop is to develop a blueprint for new frameworks to study dynamics in shape space and to foster collaborations across mathematics\, computer science\, and biology.\n\nMore Info: https://www.nitmb.org/representing-and-learning-morphology-workshop\n\nRegister: https://www.nitmb.org/representing-and-learning-morphology-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/representing-and-learning-morphology-workshop
CREATED:20250818T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20250818T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:31
DTSTART;TZID=America/Chicago:20261021T083000
DTEND;TZID=America/Chicago:20261021T170000
DTSTAMP:20260622T090637Z
SUMMARY:Representing and Learning Morphology and Shape Dynamics from Biological Data
UID:631545@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Advances in high-throughput imaging techniques now generate massive amounts of multiscale image data\, ranging from whole tissues to single cells to protein structures. Beyond static snapshots\, novel imaging methods capture long time-series that provide valuable spatio-temporal information. Analyzing this unprecedented volume of biological data raises a variety of mathematical challenges. Notably\, how can we model biological variation while disentangling biological variation from technical heterogeneity? For example\, how do single cells grow and progress through the cell cycle under diverse stimuli\, or how do proteins and molecular complexes undergo conformational changes? Despite the richness of these data\, methods for spatio-temporal analysis remain limited in computational biology. At the same time\, tools from multiple disciplines—such as deep learning in computer science\, mechanistic models in biophysics\, and dynamical systems theory in mathematics—have been developed to study related problems. In this context\, our proposed workshop will focus on theoretical and computational tools from mathematics and physics that enable rigorous analysis of spatio-temporal biological data\, with the goal of elucidating the temporal dynamics of underlying biological processes.   Intended for a diverse audience of mathematicians\, physicists\, and computational and experimental biologists\, the workshop will feature complimentary sessions on different facets of imaging data\, with a particular focus on dynamics. Our interdisciplinary organizing team will begin with a general overview of shape space\, highlighting both theoretical foundations and state-of-the-art computational tools. We will then present several publicly available datasets on protein and cell shapes from advanced imaging experiments\, and brainstorm methods to uncover the dynamics underlying observed heterogeneity. The ultimate goal of the workshop is to develop a blueprint for new frameworks to study dynamics in shape space and to foster collaborations across mathematics\, computer science\, and biology.\n\nMore Info: https://www.nitmb.org/representing-and-learning-morphology-workshop\n\nRegister: https://www.nitmb.org/representing-and-learning-morphology-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/representing-and-learning-morphology-workshop
CREATED:20250818T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20250818T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:32
DTSTART;TZID=America/Chicago:20261022T083000
DTEND;TZID=America/Chicago:20261022T170000
DTSTAMP:20260622T090637Z
SUMMARY:Representing and Learning Morphology and Shape Dynamics from Biological Data
UID:631546@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Advances in high-throughput imaging techniques now generate massive amounts of multiscale image data\, ranging from whole tissues to single cells to protein structures. Beyond static snapshots\, novel imaging methods capture long time-series that provide valuable spatio-temporal information. Analyzing this unprecedented volume of biological data raises a variety of mathematical challenges. Notably\, how can we model biological variation while disentangling biological variation from technical heterogeneity? For example\, how do single cells grow and progress through the cell cycle under diverse stimuli\, or how do proteins and molecular complexes undergo conformational changes? Despite the richness of these data\, methods for spatio-temporal analysis remain limited in computational biology. At the same time\, tools from multiple disciplines—such as deep learning in computer science\, mechanistic models in biophysics\, and dynamical systems theory in mathematics—have been developed to study related problems. In this context\, our proposed workshop will focus on theoretical and computational tools from mathematics and physics that enable rigorous analysis of spatio-temporal biological data\, with the goal of elucidating the temporal dynamics of underlying biological processes.   Intended for a diverse audience of mathematicians\, physicists\, and computational and experimental biologists\, the workshop will feature complimentary sessions on different facets of imaging data\, with a particular focus on dynamics. Our interdisciplinary organizing team will begin with a general overview of shape space\, highlighting both theoretical foundations and state-of-the-art computational tools. We will then present several publicly available datasets on protein and cell shapes from advanced imaging experiments\, and brainstorm methods to uncover the dynamics underlying observed heterogeneity. The ultimate goal of the workshop is to develop a blueprint for new frameworks to study dynamics in shape space and to foster collaborations across mathematics\, computer science\, and biology.\n\nMore Info: https://www.nitmb.org/representing-and-learning-morphology-workshop\n\nRegister: https://www.nitmb.org/representing-and-learning-morphology-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/representing-and-learning-morphology-workshop
CREATED:20250818T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20250818T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:33
DTSTART;TZID=America/Chicago:20261023T083000
DTEND;TZID=America/Chicago:20261023T170000
DTSTAMP:20260622T090637Z
SUMMARY:Representing and Learning Morphology and Shape Dynamics from Biological Data
UID:631547@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Advances in high-throughput imaging techniques now generate massive amounts of multiscale image data\, ranging from whole tissues to single cells to protein structures. Beyond static snapshots\, novel imaging methods capture long time-series that provide valuable spatio-temporal information. Analyzing this unprecedented volume of biological data raises a variety of mathematical challenges. Notably\, how can we model biological variation while disentangling biological variation from technical heterogeneity? For example\, how do single cells grow and progress through the cell cycle under diverse stimuli\, or how do proteins and molecular complexes undergo conformational changes? Despite the richness of these data\, methods for spatio-temporal analysis remain limited in computational biology. At the same time\, tools from multiple disciplines—such as deep learning in computer science\, mechanistic models in biophysics\, and dynamical systems theory in mathematics—have been developed to study related problems. In this context\, our proposed workshop will focus on theoretical and computational tools from mathematics and physics that enable rigorous analysis of spatio-temporal biological data\, with the goal of elucidating the temporal dynamics of underlying biological processes.   Intended for a diverse audience of mathematicians\, physicists\, and computational and experimental biologists\, the workshop will feature complimentary sessions on different facets of imaging data\, with a particular focus on dynamics. Our interdisciplinary organizing team will begin with a general overview of shape space\, highlighting both theoretical foundations and state-of-the-art computational tools. We will then present several publicly available datasets on protein and cell shapes from advanced imaging experiments\, and brainstorm methods to uncover the dynamics underlying observed heterogeneity. The ultimate goal of the workshop is to develop a blueprint for new frameworks to study dynamics in shape space and to foster collaborations across mathematics\, computer science\, and biology.\n\nMore Info: https://www.nitmb.org/representing-and-learning-morphology-workshop\n\nRegister: https://www.nitmb.org/representing-and-learning-morphology-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/representing-and-learning-morphology-workshop
CREATED:20250818T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20250818T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:34
DTSTART;VALUE=DATE:20261026
DTEND;VALUE=DATE:20261027
DTSTAMP:20260622T090637Z
SUMMARY:NITMB Scientific Focus: Theory and Mathematics in Neuroscience  Geometry in Neuroscience Workshop
UID:642768@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Recent advances in neuroscience reveal that neural activity often exhibits striking geometric structure across sensory\, cognitive\, and motor systems. For instance\, low-dimensional neural activity manifolds encode behavioral and cognitive variables in many brain regions\, and these manifolds can vary less across time\, individuals\, and species than single neuron activity. These findings suggest that geometry is fundamental to neural computation and may provide a unifying perspective on how neural systems represent information\, perform computations\, and support behavior.​  This workshop will bring together experimentalists\, theorists\, and mathematicians to identify geometric principles underlying neural computation\, highlight open mathematical challenges\, and foster collaborations at the interface of neuroscience and geometry. Neuroscience topics will include representational geometry in neural population activity\, the structure and function of neural manifolds\, the geometry of parameter landscapes underlying neural computation and learning\, and geometric and topological approaches to high-dimensional neural data. The workshop aims to both highlight existing mathematical ideas in neuroscience and identify new mathematical questions inspired by neural systems. Relevant areas of mathematics include differential geometry\, topology\, dynamical systems\, optimization\, and information geometry. The program will include invited talks\, focused discussions\, and opportunities for informal exchange aimed at developing a common language for describing neural systems in geometric terms.  Part of the NITMB Scientific Focus: Theory and Mathematics in Neuroscience\n\nMore Info: https://www.nitmb.org/geometry-in-neuroscience-workshop\n\nRegister: https://www.nitmb.org/geometry-in-neuroscience-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/geometry-in-neuroscience-workshop
CREATED:20260604T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260604T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:35
DTSTART;VALUE=DATE:20261027
DTEND;VALUE=DATE:20261028
DTSTAMP:20260622T090637Z
SUMMARY:NITMB Scientific Focus: Theory and Mathematics in Neuroscience  Geometry in Neuroscience Workshop
UID:642769@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Recent advances in neuroscience reveal that neural activity often exhibits striking geometric structure across sensory\, cognitive\, and motor systems. For instance\, low-dimensional neural activity manifolds encode behavioral and cognitive variables in many brain regions\, and these manifolds can vary less across time\, individuals\, and species than single neuron activity. These findings suggest that geometry is fundamental to neural computation and may provide a unifying perspective on how neural systems represent information\, perform computations\, and support behavior.​  This workshop will bring together experimentalists\, theorists\, and mathematicians to identify geometric principles underlying neural computation\, highlight open mathematical challenges\, and foster collaborations at the interface of neuroscience and geometry. Neuroscience topics will include representational geometry in neural population activity\, the structure and function of neural manifolds\, the geometry of parameter landscapes underlying neural computation and learning\, and geometric and topological approaches to high-dimensional neural data. The workshop aims to both highlight existing mathematical ideas in neuroscience and identify new mathematical questions inspired by neural systems. Relevant areas of mathematics include differential geometry\, topology\, dynamical systems\, optimization\, and information geometry. The program will include invited talks\, focused discussions\, and opportunities for informal exchange aimed at developing a common language for describing neural systems in geometric terms.  Part of the NITMB Scientific Focus: Theory and Mathematics in Neuroscience\n\nMore Info: https://www.nitmb.org/geometry-in-neuroscience-workshop\n\nRegister: https://www.nitmb.org/geometry-in-neuroscience-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/geometry-in-neuroscience-workshop
CREATED:20260604T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260604T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:36
DTSTART;VALUE=DATE:20261028
DTEND;VALUE=DATE:20261029
DTSTAMP:20260622T090637Z
SUMMARY:NITMB Scientific Focus: Theory and Mathematics in Neuroscience  Geometry in Neuroscience Workshop
UID:642770@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Recent advances in neuroscience reveal that neural activity often exhibits striking geometric structure across sensory\, cognitive\, and motor systems. For instance\, low-dimensional neural activity manifolds encode behavioral and cognitive variables in many brain regions\, and these manifolds can vary less across time\, individuals\, and species than single neuron activity. These findings suggest that geometry is fundamental to neural computation and may provide a unifying perspective on how neural systems represent information\, perform computations\, and support behavior.​  This workshop will bring together experimentalists\, theorists\, and mathematicians to identify geometric principles underlying neural computation\, highlight open mathematical challenges\, and foster collaborations at the interface of neuroscience and geometry. Neuroscience topics will include representational geometry in neural population activity\, the structure and function of neural manifolds\, the geometry of parameter landscapes underlying neural computation and learning\, and geometric and topological approaches to high-dimensional neural data. The workshop aims to both highlight existing mathematical ideas in neuroscience and identify new mathematical questions inspired by neural systems. Relevant areas of mathematics include differential geometry\, topology\, dynamical systems\, optimization\, and information geometry. The program will include invited talks\, focused discussions\, and opportunities for informal exchange aimed at developing a common language for describing neural systems in geometric terms.  Part of the NITMB Scientific Focus: Theory and Mathematics in Neuroscience\n\nMore Info: https://www.nitmb.org/geometry-in-neuroscience-workshop\n\nRegister: https://www.nitmb.org/geometry-in-neuroscience-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/geometry-in-neuroscience-workshop
CREATED:20260604T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260604T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:37
DTSTART;VALUE=DATE:20261109
DTEND;VALUE=DATE:20261110
DTSTAMP:20260622T090637Z
SUMMARY:Multi-scale Biological Adaptation to Environmental Variability
UID:636026@northwestern.edu
TZID:America/Chicago
DESCRIPTION:More information - https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability  Understanding how complex\, multi-scale biological systems operate in a constantly changing environment is a challenging scientific problem. One important issue is that the relevant scales span separate fields of research\, such as genetics\, cellular biology\, physiology\, neurobiology\, and ecology—disciplines that use largely different methods and experimental models. This is an important limitation because biological systems are inherently multi-scale and involve complex coordination across scales. Moreover\, we currently lack the theoretical and experimental framework to understand the impact of an unpredictable environment on organismal and supra-organismal responses.   Mathematical approaches will play a critical role in modeling and predicting the complex\, often multifaceted effects of environmental variability on biology across scales. Adapting existing mathematical models and developing new methods to capture the multi-scale effects of environmental variability is not a trivial task\, especially when we are only beginning to document its impact on biological systems across scales.  This workshop will bring together 75 scientists working across the fields of experimental biology\, mathematics\, theoretical biology\, and experts in complex systems to discuss the effects of photoperiod\, temperature\, seasonality\, and other types of environmental variability on the function of the nervous system\, on organismal physiology\, and on super-organismal responses\, such as those that occur at the level of ecology and population dynamics.\n\nMore Info: https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability
CREATED:20251113T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20251113T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:38
DTSTART;VALUE=DATE:20261110
DTEND;VALUE=DATE:20261111
DTSTAMP:20260622T090637Z
SUMMARY:Multi-scale Biological Adaptation to Environmental Variability
UID:636027@northwestern.edu
TZID:America/Chicago
DESCRIPTION:More information - https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability  Understanding how complex\, multi-scale biological systems operate in a constantly changing environment is a challenging scientific problem. One important issue is that the relevant scales span separate fields of research\, such as genetics\, cellular biology\, physiology\, neurobiology\, and ecology—disciplines that use largely different methods and experimental models. This is an important limitation because biological systems are inherently multi-scale and involve complex coordination across scales. Moreover\, we currently lack the theoretical and experimental framework to understand the impact of an unpredictable environment on organismal and supra-organismal responses.   Mathematical approaches will play a critical role in modeling and predicting the complex\, often multifaceted effects of environmental variability on biology across scales. Adapting existing mathematical models and developing new methods to capture the multi-scale effects of environmental variability is not a trivial task\, especially when we are only beginning to document its impact on biological systems across scales.  This workshop will bring together 75 scientists working across the fields of experimental biology\, mathematics\, theoretical biology\, and experts in complex systems to discuss the effects of photoperiod\, temperature\, seasonality\, and other types of environmental variability on the function of the nervous system\, on organismal physiology\, and on super-organismal responses\, such as those that occur at the level of ecology and population dynamics.\n\nMore Info: https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability
CREATED:20251113T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20251113T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:39
DTSTART;VALUE=DATE:20261111
DTEND;VALUE=DATE:20261112
DTSTAMP:20260622T090637Z
SUMMARY:Multi-scale Biological Adaptation to Environmental Variability
UID:636028@northwestern.edu
TZID:America/Chicago
DESCRIPTION:More information - https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability  Understanding how complex\, multi-scale biological systems operate in a constantly changing environment is a challenging scientific problem. One important issue is that the relevant scales span separate fields of research\, such as genetics\, cellular biology\, physiology\, neurobiology\, and ecology—disciplines that use largely different methods and experimental models. This is an important limitation because biological systems are inherently multi-scale and involve complex coordination across scales. Moreover\, we currently lack the theoretical and experimental framework to understand the impact of an unpredictable environment on organismal and supra-organismal responses.   Mathematical approaches will play a critical role in modeling and predicting the complex\, often multifaceted effects of environmental variability on biology across scales. Adapting existing mathematical models and developing new methods to capture the multi-scale effects of environmental variability is not a trivial task\, especially when we are only beginning to document its impact on biological systems across scales.  This workshop will bring together 75 scientists working across the fields of experimental biology\, mathematics\, theoretical biology\, and experts in complex systems to discuss the effects of photoperiod\, temperature\, seasonality\, and other types of environmental variability on the function of the nervous system\, on organismal physiology\, and on super-organismal responses\, such as those that occur at the level of ecology and population dynamics.\n\nMore Info: https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability
CREATED:20251113T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20251113T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:40
DTSTART;VALUE=DATE:20261112
DTEND;VALUE=DATE:20261113
DTSTAMP:20260622T090637Z
SUMMARY:Multi-scale Biological Adaptation to Environmental Variability
UID:636029@northwestern.edu
TZID:America/Chicago
DESCRIPTION:More information - https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability  Understanding how complex\, multi-scale biological systems operate in a constantly changing environment is a challenging scientific problem. One important issue is that the relevant scales span separate fields of research\, such as genetics\, cellular biology\, physiology\, neurobiology\, and ecology—disciplines that use largely different methods and experimental models. This is an important limitation because biological systems are inherently multi-scale and involve complex coordination across scales. Moreover\, we currently lack the theoretical and experimental framework to understand the impact of an unpredictable environment on organismal and supra-organismal responses.   Mathematical approaches will play a critical role in modeling and predicting the complex\, often multifaceted effects of environmental variability on biology across scales. Adapting existing mathematical models and developing new methods to capture the multi-scale effects of environmental variability is not a trivial task\, especially when we are only beginning to document its impact on biological systems across scales.  This workshop will bring together 75 scientists working across the fields of experimental biology\, mathematics\, theoretical biology\, and experts in complex systems to discuss the effects of photoperiod\, temperature\, seasonality\, and other types of environmental variability on the function of the nervous system\, on organismal physiology\, and on super-organismal responses\, such as those that occur at the level of ecology and population dynamics.\n\nMore Info: https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability
CREATED:20251113T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20251113T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:41
DTSTART;VALUE=DATE:20261113
DTEND;VALUE=DATE:20261114
DTSTAMP:20260622T090637Z
SUMMARY:Multi-scale Biological Adaptation to Environmental Variability
UID:636030@northwestern.edu
TZID:America/Chicago
DESCRIPTION:More information - https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability  Understanding how complex\, multi-scale biological systems operate in a constantly changing environment is a challenging scientific problem. One important issue is that the relevant scales span separate fields of research\, such as genetics\, cellular biology\, physiology\, neurobiology\, and ecology—disciplines that use largely different methods and experimental models. This is an important limitation because biological systems are inherently multi-scale and involve complex coordination across scales. Moreover\, we currently lack the theoretical and experimental framework to understand the impact of an unpredictable environment on organismal and supra-organismal responses.   Mathematical approaches will play a critical role in modeling and predicting the complex\, often multifaceted effects of environmental variability on biology across scales. Adapting existing mathematical models and developing new methods to capture the multi-scale effects of environmental variability is not a trivial task\, especially when we are only beginning to document its impact on biological systems across scales.  This workshop will bring together 75 scientists working across the fields of experimental biology\, mathematics\, theoretical biology\, and experts in complex systems to discuss the effects of photoperiod\, temperature\, seasonality\, and other types of environmental variability on the function of the nervous system\, on organismal physiology\, and on super-organismal responses\, such as those that occur at the level of ecology and population dynamics.\n\nMore Info: https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/multiscale-biological-adaptation-to-environmental-variability
CREATED:20251113T060000Z
STATUS:CONFIRMED
LAST-MODIFIED:20251113T060000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:42
DTSTART;VALUE=DATE:20270201
DTEND;VALUE=DATE:20270202
DTSTAMP:20260622T090637Z
SUMMARY:Image-Based Scientific Machine Learning for Advancing Theory in Biology
UID:642771@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Modern imaging now allows us to observe living systems across molecular\, cellular\, and tissue scales with unprecedented precision\, yet our ability to extract mechanistic understanding from these data remains limited. Unlike molecular omics data\, imaging captures continuous high-dimensional spatiotemporal information (e.g.\, shape\, motion) that is inherently complex to represent\, analyze\, and interpret. There is a deluge of such data\, but it remains a challenge to transform such data into interpretable quantitative models and to link them to multimodal data (proteomics\, genomics\, metabolomics) to reveal the governing principles of biological organization across scales. This workshop will address that challenge by bringing together mathematicians\, computer scientists\, physicists\, and biologists to accelerate the development of image-based scientific machine learning (ML) for biological dynamics — methods capable of learning “laws” of biology directly from experimental images and movies and yielding new insight into how complex forms and behaviors emerge from subcellular structures to whole organs.​  Several interconnected goals will be pursued: developing physics-informed ML frameworks that embed physical priors such as conservation laws\, symmetries\, and force balance directly into learning from imaging data; inferring dynamical rules and governing equations from spatiotemporal observations; building principled approaches to bridge scales from subcellular mechanics to tissue and organ morphogenesis; defining cell states and understanding their transitions — how cells move through state space\, commit to new identities\, and undergo rare but important events such as differentiation decisions and symmetry-breaking; and integrating imaging data with single-cell genomics and spatial transcriptomics to link geometry\, mechanics\, and motion with molecular state. Practically\, the workshop will work toward shared benchmarks\, open tools\, and community datasets that allow rigorous comparison of new methods and lower the barrier for experimental biologists to use them. Underlying all of this is a meta-goal: cultivating a shared cross-disciplinary language and problem formulation that allows researchers from diverse communities to collaborate productively\, laying the foundation for a new era of ML-enabled scientific discovery and theory-building in biology.  Part of the Image-Based Scientific Machine Learning for Theories of Biological Dynamics Across Scales Long Program\n\nMore Info: https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology\n\nRegister: https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology
CREATED:20260604T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260604T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:43
DTSTART;VALUE=DATE:20270202
DTEND;VALUE=DATE:20270203
DTSTAMP:20260622T090637Z
SUMMARY:Image-Based Scientific Machine Learning for Advancing Theory in Biology
UID:642772@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Modern imaging now allows us to observe living systems across molecular\, cellular\, and tissue scales with unprecedented precision\, yet our ability to extract mechanistic understanding from these data remains limited. Unlike molecular omics data\, imaging captures continuous high-dimensional spatiotemporal information (e.g.\, shape\, motion) that is inherently complex to represent\, analyze\, and interpret. There is a deluge of such data\, but it remains a challenge to transform such data into interpretable quantitative models and to link them to multimodal data (proteomics\, genomics\, metabolomics) to reveal the governing principles of biological organization across scales. This workshop will address that challenge by bringing together mathematicians\, computer scientists\, physicists\, and biologists to accelerate the development of image-based scientific machine learning (ML) for biological dynamics — methods capable of learning “laws” of biology directly from experimental images and movies and yielding new insight into how complex forms and behaviors emerge from subcellular structures to whole organs.​  Several interconnected goals will be pursued: developing physics-informed ML frameworks that embed physical priors such as conservation laws\, symmetries\, and force balance directly into learning from imaging data; inferring dynamical rules and governing equations from spatiotemporal observations; building principled approaches to bridge scales from subcellular mechanics to tissue and organ morphogenesis; defining cell states and understanding their transitions — how cells move through state space\, commit to new identities\, and undergo rare but important events such as differentiation decisions and symmetry-breaking; and integrating imaging data with single-cell genomics and spatial transcriptomics to link geometry\, mechanics\, and motion with molecular state. Practically\, the workshop will work toward shared benchmarks\, open tools\, and community datasets that allow rigorous comparison of new methods and lower the barrier for experimental biologists to use them. Underlying all of this is a meta-goal: cultivating a shared cross-disciplinary language and problem formulation that allows researchers from diverse communities to collaborate productively\, laying the foundation for a new era of ML-enabled scientific discovery and theory-building in biology.  Part of the Image-Based Scientific Machine Learning for Theories of Biological Dynamics Across Scales Long Program\n\nMore Info: https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology\n\nRegister: https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology
CREATED:20260604T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260604T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:44
DTSTART;VALUE=DATE:20270203
DTEND;VALUE=DATE:20270204
DTSTAMP:20260622T090637Z
SUMMARY:Image-Based Scientific Machine Learning for Advancing Theory in Biology
UID:642773@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Modern imaging now allows us to observe living systems across molecular\, cellular\, and tissue scales with unprecedented precision\, yet our ability to extract mechanistic understanding from these data remains limited. Unlike molecular omics data\, imaging captures continuous high-dimensional spatiotemporal information (e.g.\, shape\, motion) that is inherently complex to represent\, analyze\, and interpret. There is a deluge of such data\, but it remains a challenge to transform such data into interpretable quantitative models and to link them to multimodal data (proteomics\, genomics\, metabolomics) to reveal the governing principles of biological organization across scales. This workshop will address that challenge by bringing together mathematicians\, computer scientists\, physicists\, and biologists to accelerate the development of image-based scientific machine learning (ML) for biological dynamics — methods capable of learning “laws” of biology directly from experimental images and movies and yielding new insight into how complex forms and behaviors emerge from subcellular structures to whole organs.​  Several interconnected goals will be pursued: developing physics-informed ML frameworks that embed physical priors such as conservation laws\, symmetries\, and force balance directly into learning from imaging data; inferring dynamical rules and governing equations from spatiotemporal observations; building principled approaches to bridge scales from subcellular mechanics to tissue and organ morphogenesis; defining cell states and understanding their transitions — how cells move through state space\, commit to new identities\, and undergo rare but important events such as differentiation decisions and symmetry-breaking; and integrating imaging data with single-cell genomics and spatial transcriptomics to link geometry\, mechanics\, and motion with molecular state. Practically\, the workshop will work toward shared benchmarks\, open tools\, and community datasets that allow rigorous comparison of new methods and lower the barrier for experimental biologists to use them. Underlying all of this is a meta-goal: cultivating a shared cross-disciplinary language and problem formulation that allows researchers from diverse communities to collaborate productively\, laying the foundation for a new era of ML-enabled scientific discovery and theory-building in biology.  Part of the Image-Based Scientific Machine Learning for Theories of Biological Dynamics Across Scales Long Program\n\nMore Info: https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology\n\nRegister: https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology
CREATED:20260604T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260604T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:45
DTSTART;VALUE=DATE:20270204
DTEND;VALUE=DATE:20270205
DTSTAMP:20260622T090637Z
SUMMARY:Image-Based Scientific Machine Learning for Advancing Theory in Biology
UID:642774@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Modern imaging now allows us to observe living systems across molecular\, cellular\, and tissue scales with unprecedented precision\, yet our ability to extract mechanistic understanding from these data remains limited. Unlike molecular omics data\, imaging captures continuous high-dimensional spatiotemporal information (e.g.\, shape\, motion) that is inherently complex to represent\, analyze\, and interpret. There is a deluge of such data\, but it remains a challenge to transform such data into interpretable quantitative models and to link them to multimodal data (proteomics\, genomics\, metabolomics) to reveal the governing principles of biological organization across scales. This workshop will address that challenge by bringing together mathematicians\, computer scientists\, physicists\, and biologists to accelerate the development of image-based scientific machine learning (ML) for biological dynamics — methods capable of learning “laws” of biology directly from experimental images and movies and yielding new insight into how complex forms and behaviors emerge from subcellular structures to whole organs.​  Several interconnected goals will be pursued: developing physics-informed ML frameworks that embed physical priors such as conservation laws\, symmetries\, and force balance directly into learning from imaging data; inferring dynamical rules and governing equations from spatiotemporal observations; building principled approaches to bridge scales from subcellular mechanics to tissue and organ morphogenesis; defining cell states and understanding their transitions — how cells move through state space\, commit to new identities\, and undergo rare but important events such as differentiation decisions and symmetry-breaking; and integrating imaging data with single-cell genomics and spatial transcriptomics to link geometry\, mechanics\, and motion with molecular state. Practically\, the workshop will work toward shared benchmarks\, open tools\, and community datasets that allow rigorous comparison of new methods and lower the barrier for experimental biologists to use them. Underlying all of this is a meta-goal: cultivating a shared cross-disciplinary language and problem formulation that allows researchers from diverse communities to collaborate productively\, laying the foundation for a new era of ML-enabled scientific discovery and theory-building in biology.  Part of the Image-Based Scientific Machine Learning for Theories of Biological Dynamics Across Scales Long Program\n\nMore Info: https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology\n\nRegister: https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology
CREATED:20260604T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260604T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:46
DTSTART;VALUE=DATE:20270205
DTEND;VALUE=DATE:20270206
DTSTAMP:20260622T090637Z
SUMMARY:Image-Based Scientific Machine Learning for Advancing Theory in Biology
UID:642775@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Modern imaging now allows us to observe living systems across molecular\, cellular\, and tissue scales with unprecedented precision\, yet our ability to extract mechanistic understanding from these data remains limited. Unlike molecular omics data\, imaging captures continuous high-dimensional spatiotemporal information (e.g.\, shape\, motion) that is inherently complex to represent\, analyze\, and interpret. There is a deluge of such data\, but it remains a challenge to transform such data into interpretable quantitative models and to link them to multimodal data (proteomics\, genomics\, metabolomics) to reveal the governing principles of biological organization across scales. This workshop will address that challenge by bringing together mathematicians\, computer scientists\, physicists\, and biologists to accelerate the development of image-based scientific machine learning (ML) for biological dynamics — methods capable of learning “laws” of biology directly from experimental images and movies and yielding new insight into how complex forms and behaviors emerge from subcellular structures to whole organs.​  Several interconnected goals will be pursued: developing physics-informed ML frameworks that embed physical priors such as conservation laws\, symmetries\, and force balance directly into learning from imaging data; inferring dynamical rules and governing equations from spatiotemporal observations; building principled approaches to bridge scales from subcellular mechanics to tissue and organ morphogenesis; defining cell states and understanding their transitions — how cells move through state space\, commit to new identities\, and undergo rare but important events such as differentiation decisions and symmetry-breaking; and integrating imaging data with single-cell genomics and spatial transcriptomics to link geometry\, mechanics\, and motion with molecular state. Practically\, the workshop will work toward shared benchmarks\, open tools\, and community datasets that allow rigorous comparison of new methods and lower the barrier for experimental biologists to use them. Underlying all of this is a meta-goal: cultivating a shared cross-disciplinary language and problem formulation that allows researchers from diverse communities to collaborate productively\, laying the foundation for a new era of ML-enabled scientific discovery and theory-building in biology.  Part of the Image-Based Scientific Machine Learning for Theories of Biological Dynamics Across Scales Long Program\n\nMore Info: https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology\n\nRegister: https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/image-based-scientific-machine-learning-for-advancing-theory-in-biology
CREATED:20260604T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260604T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:47
DTSTART;TZID=America/Chicago:20270405T083000
DTEND;TZID=America/Chicago:20270405T170000
DTSTAMP:20260622T090637Z
SUMMARY:Biological Oscillators Across Cellular\, Temporal\, and Spatial Scales
UID:641894@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Oscillatory dynamics are a fundamental feature of biological systems\, spanning spatial and temporal scales from single cells to tissues and whole organisms. These oscillators exhibit diverse behaviors—including cell-autonomous or coupled dynamics\, synchronous or asynchronous modes\, and stable\, excitable\, or adaptive regimes. While the molecular mechanisms underlying many biological oscillators are increasingly well understood\, the general principles governing the emergence\, robustness\, and functional diversity of oscillatory behavior remain incomplete.  Recent advances in experimental methods—such as high-resolution live-cell imaging\, quantitative perturbations\, advanced image analysis\, and human pluripotent stem cell–based model systems—enable unprecedented quantitative interrogation of oscillatory phenomena. In parallel\, mathematical biology has become essential for understanding how noise\, coupling\, and cell–cell communication shape oscillatory dynamics. This workshop seeks to integrate experimental and theoretical perspectives\, fostering interactions in which biological observations motivate new mathematical frameworks and mathematical theory informs experimental design and interpretation.  By bridging disciplines\, the workshop aims to advance multiple fields\, including chronobiology\, evolutionary biology\, and mathematical biology. Participants will examine how oscillatory signals are generated\, interpreted\, and deployed to regulate cellular fate decisions and coordinate collective behaviors across scales. Through critical evaluation of current models and identification of open challenges\, the workshop will catalyze new collaborations and modeling approaches\, leading to testable predictions and deeper insights into biological oscillators.\n\nMore Info: https://www.nitmb.org/biological-oscillators-workshop-2027
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/biological-oscillators-workshop-2027
CREATED:20260422T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260422T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:48
DTSTART;TZID=America/Chicago:20270406T083000
DTEND;TZID=America/Chicago:20270406T170000
DTSTAMP:20260622T090637Z
SUMMARY:Biological Oscillators Across Cellular\, Temporal\, and Spatial Scales
UID:641895@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Oscillatory dynamics are a fundamental feature of biological systems\, spanning spatial and temporal scales from single cells to tissues and whole organisms. These oscillators exhibit diverse behaviors—including cell-autonomous or coupled dynamics\, synchronous or asynchronous modes\, and stable\, excitable\, or adaptive regimes. While the molecular mechanisms underlying many biological oscillators are increasingly well understood\, the general principles governing the emergence\, robustness\, and functional diversity of oscillatory behavior remain incomplete.  Recent advances in experimental methods—such as high-resolution live-cell imaging\, quantitative perturbations\, advanced image analysis\, and human pluripotent stem cell–based model systems—enable unprecedented quantitative interrogation of oscillatory phenomena. In parallel\, mathematical biology has become essential for understanding how noise\, coupling\, and cell–cell communication shape oscillatory dynamics. This workshop seeks to integrate experimental and theoretical perspectives\, fostering interactions in which biological observations motivate new mathematical frameworks and mathematical theory informs experimental design and interpretation.  By bridging disciplines\, the workshop aims to advance multiple fields\, including chronobiology\, evolutionary biology\, and mathematical biology. Participants will examine how oscillatory signals are generated\, interpreted\, and deployed to regulate cellular fate decisions and coordinate collective behaviors across scales. Through critical evaluation of current models and identification of open challenges\, the workshop will catalyze new collaborations and modeling approaches\, leading to testable predictions and deeper insights into biological oscillators.\n\nMore Info: https://www.nitmb.org/biological-oscillators-workshop-2027
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/biological-oscillators-workshop-2027
CREATED:20260422T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260422T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:49
DTSTART;TZID=America/Chicago:20270407T083000
DTEND;TZID=America/Chicago:20270407T170000
DTSTAMP:20260622T090637Z
SUMMARY:Biological Oscillators Across Cellular\, Temporal\, and Spatial Scales
UID:641896@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Oscillatory dynamics are a fundamental feature of biological systems\, spanning spatial and temporal scales from single cells to tissues and whole organisms. These oscillators exhibit diverse behaviors—including cell-autonomous or coupled dynamics\, synchronous or asynchronous modes\, and stable\, excitable\, or adaptive regimes. While the molecular mechanisms underlying many biological oscillators are increasingly well understood\, the general principles governing the emergence\, robustness\, and functional diversity of oscillatory behavior remain incomplete.  Recent advances in experimental methods—such as high-resolution live-cell imaging\, quantitative perturbations\, advanced image analysis\, and human pluripotent stem cell–based model systems—enable unprecedented quantitative interrogation of oscillatory phenomena. In parallel\, mathematical biology has become essential for understanding how noise\, coupling\, and cell–cell communication shape oscillatory dynamics. This workshop seeks to integrate experimental and theoretical perspectives\, fostering interactions in which biological observations motivate new mathematical frameworks and mathematical theory informs experimental design and interpretation.  By bridging disciplines\, the workshop aims to advance multiple fields\, including chronobiology\, evolutionary biology\, and mathematical biology. Participants will examine how oscillatory signals are generated\, interpreted\, and deployed to regulate cellular fate decisions and coordinate collective behaviors across scales. Through critical evaluation of current models and identification of open challenges\, the workshop will catalyze new collaborations and modeling approaches\, leading to testable predictions and deeper insights into biological oscillators.\n\nMore Info: https://www.nitmb.org/biological-oscillators-workshop-2027
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/biological-oscillators-workshop-2027
CREATED:20260422T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260422T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:50
DTSTART;TZID=America/Chicago:20270408T083000
DTEND;TZID=America/Chicago:20270408T170000
DTSTAMP:20260622T090637Z
SUMMARY:Biological Oscillators Across Cellular\, Temporal\, and Spatial Scales
UID:641897@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Oscillatory dynamics are a fundamental feature of biological systems\, spanning spatial and temporal scales from single cells to tissues and whole organisms. These oscillators exhibit diverse behaviors—including cell-autonomous or coupled dynamics\, synchronous or asynchronous modes\, and stable\, excitable\, or adaptive regimes. While the molecular mechanisms underlying many biological oscillators are increasingly well understood\, the general principles governing the emergence\, robustness\, and functional diversity of oscillatory behavior remain incomplete.  Recent advances in experimental methods—such as high-resolution live-cell imaging\, quantitative perturbations\, advanced image analysis\, and human pluripotent stem cell–based model systems—enable unprecedented quantitative interrogation of oscillatory phenomena. In parallel\, mathematical biology has become essential for understanding how noise\, coupling\, and cell–cell communication shape oscillatory dynamics. This workshop seeks to integrate experimental and theoretical perspectives\, fostering interactions in which biological observations motivate new mathematical frameworks and mathematical theory informs experimental design and interpretation.  By bridging disciplines\, the workshop aims to advance multiple fields\, including chronobiology\, evolutionary biology\, and mathematical biology. Participants will examine how oscillatory signals are generated\, interpreted\, and deployed to regulate cellular fate decisions and coordinate collective behaviors across scales. Through critical evaluation of current models and identification of open challenges\, the workshop will catalyze new collaborations and modeling approaches\, leading to testable predictions and deeper insights into biological oscillators.\n\nMore Info: https://www.nitmb.org/biological-oscillators-workshop-2027
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/biological-oscillators-workshop-2027
CREATED:20260422T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260422T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:51
DTSTART;TZID=America/Chicago:20270409T083000
DTEND;TZID=America/Chicago:20270409T170000
DTSTAMP:20260622T090637Z
SUMMARY:Biological Oscillators Across Cellular\, Temporal\, and Spatial Scales
UID:641898@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Oscillatory dynamics are a fundamental feature of biological systems\, spanning spatial and temporal scales from single cells to tissues and whole organisms. These oscillators exhibit diverse behaviors—including cell-autonomous or coupled dynamics\, synchronous or asynchronous modes\, and stable\, excitable\, or adaptive regimes. While the molecular mechanisms underlying many biological oscillators are increasingly well understood\, the general principles governing the emergence\, robustness\, and functional diversity of oscillatory behavior remain incomplete.  Recent advances in experimental methods—such as high-resolution live-cell imaging\, quantitative perturbations\, advanced image analysis\, and human pluripotent stem cell–based model systems—enable unprecedented quantitative interrogation of oscillatory phenomena. In parallel\, mathematical biology has become essential for understanding how noise\, coupling\, and cell–cell communication shape oscillatory dynamics. This workshop seeks to integrate experimental and theoretical perspectives\, fostering interactions in which biological observations motivate new mathematical frameworks and mathematical theory informs experimental design and interpretation.  By bridging disciplines\, the workshop aims to advance multiple fields\, including chronobiology\, evolutionary biology\, and mathematical biology. Participants will examine how oscillatory signals are generated\, interpreted\, and deployed to regulate cellular fate decisions and coordinate collective behaviors across scales. Through critical evaluation of current models and identification of open challenges\, the workshop will catalyze new collaborations and modeling approaches\, leading to testable predictions and deeper insights into biological oscillators.\n\nMore Info: https://www.nitmb.org/biological-oscillators-workshop-2027
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/biological-oscillators-workshop-2027
CREATED:20260422T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260422T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:52
DTSTART;TZID=America/Chicago:20270503T083000
DTEND;TZID=America/Chicago:20270503T170000
DTSTAMP:20260622T090637Z
SUMMARY:Phylogenetics Meets Population Genetics: From Trees to Networks
UID:642084@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Understanding evolutionary history from genetic data is a central challenge in modern biology. Traditionally\, phylogenetics and population genetics have approached this problem at different scales\, phylogenetics focusing on relationships among species over long timescales\, and population genetics examining processes within species over shorter timescales. However\, the rapid growth of genome-scale data is blurring these boundaries and revealing increasingly complex\, non-treelike patterns of evolution driven by recombination\, gene flow\, and hybridization.   This workshop will bring together researchers from mathematics\, statistics\, and biology to explore the shared foundations of these fields and to develop new integrative approaches for modeling and inference. A particular focus will be on connections between ancestral recombination graphs and phylogenetic networks\, which\, despite arising in different contexts\, are mathematically equivalent structures used to represent reticulate evolutionary histories. ​  The program will emphasize collaboration and discussion\, featuring a tutorial day to establish common ground across disciplines\, followed by time for focused working group sessions as well as research presentations. Participants will identify key challenges\, compare modeling frameworks\, and initiate new research directions at the interface of stochastic processes\, graph theory\, and evolutionary biology.\n\nMore Info: https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop\n\nRegister: https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop
CREATED:20260505T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260505T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:53
DTSTART;TZID=America/Chicago:20270504T083000
DTEND;TZID=America/Chicago:20270504T170000
DTSTAMP:20260622T090637Z
SUMMARY:Phylogenetics Meets Population Genetics: From Trees to Networks
UID:642085@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Understanding evolutionary history from genetic data is a central challenge in modern biology. Traditionally\, phylogenetics and population genetics have approached this problem at different scales\, phylogenetics focusing on relationships among species over long timescales\, and population genetics examining processes within species over shorter timescales. However\, the rapid growth of genome-scale data is blurring these boundaries and revealing increasingly complex\, non-treelike patterns of evolution driven by recombination\, gene flow\, and hybridization.   This workshop will bring together researchers from mathematics\, statistics\, and biology to explore the shared foundations of these fields and to develop new integrative approaches for modeling and inference. A particular focus will be on connections between ancestral recombination graphs and phylogenetic networks\, which\, despite arising in different contexts\, are mathematically equivalent structures used to represent reticulate evolutionary histories. ​  The program will emphasize collaboration and discussion\, featuring a tutorial day to establish common ground across disciplines\, followed by time for focused working group sessions as well as research presentations. Participants will identify key challenges\, compare modeling frameworks\, and initiate new research directions at the interface of stochastic processes\, graph theory\, and evolutionary biology.\n\nMore Info: https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop\n\nRegister: https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop
CREATED:20260505T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260505T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:54
DTSTART;TZID=America/Chicago:20270505T083000
DTEND;TZID=America/Chicago:20270505T170000
DTSTAMP:20260622T090637Z
SUMMARY:Phylogenetics Meets Population Genetics: From Trees to Networks
UID:642086@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Understanding evolutionary history from genetic data is a central challenge in modern biology. Traditionally\, phylogenetics and population genetics have approached this problem at different scales\, phylogenetics focusing on relationships among species over long timescales\, and population genetics examining processes within species over shorter timescales. However\, the rapid growth of genome-scale data is blurring these boundaries and revealing increasingly complex\, non-treelike patterns of evolution driven by recombination\, gene flow\, and hybridization.   This workshop will bring together researchers from mathematics\, statistics\, and biology to explore the shared foundations of these fields and to develop new integrative approaches for modeling and inference. A particular focus will be on connections between ancestral recombination graphs and phylogenetic networks\, which\, despite arising in different contexts\, are mathematically equivalent structures used to represent reticulate evolutionary histories. ​  The program will emphasize collaboration and discussion\, featuring a tutorial day to establish common ground across disciplines\, followed by time for focused working group sessions as well as research presentations. Participants will identify key challenges\, compare modeling frameworks\, and initiate new research directions at the interface of stochastic processes\, graph theory\, and evolutionary biology.\n\nMore Info: https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop\n\nRegister: https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop
CREATED:20260505T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260505T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:55
DTSTART;TZID=America/Chicago:20270506T083000
DTEND;TZID=America/Chicago:20270506T170000
DTSTAMP:20260622T090637Z
SUMMARY:Phylogenetics Meets Population Genetics: From Trees to Networks
UID:642087@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Understanding evolutionary history from genetic data is a central challenge in modern biology. Traditionally\, phylogenetics and population genetics have approached this problem at different scales\, phylogenetics focusing on relationships among species over long timescales\, and population genetics examining processes within species over shorter timescales. However\, the rapid growth of genome-scale data is blurring these boundaries and revealing increasingly complex\, non-treelike patterns of evolution driven by recombination\, gene flow\, and hybridization.   This workshop will bring together researchers from mathematics\, statistics\, and biology to explore the shared foundations of these fields and to develop new integrative approaches for modeling and inference. A particular focus will be on connections between ancestral recombination graphs and phylogenetic networks\, which\, despite arising in different contexts\, are mathematically equivalent structures used to represent reticulate evolutionary histories. ​  The program will emphasize collaboration and discussion\, featuring a tutorial day to establish common ground across disciplines\, followed by time for focused working group sessions as well as research presentations. Participants will identify key challenges\, compare modeling frameworks\, and initiate new research directions at the interface of stochastic processes\, graph theory\, and evolutionary biology.\n\nMore Info: https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop\n\nRegister: https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop
CREATED:20260505T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260505T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:56
DTSTART;TZID=America/Chicago:20270507T083000
DTEND;TZID=America/Chicago:20270507T170000
DTSTAMP:20260622T090637Z
SUMMARY:Phylogenetics Meets Population Genetics: From Trees to Networks
UID:642088@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Understanding evolutionary history from genetic data is a central challenge in modern biology. Traditionally\, phylogenetics and population genetics have approached this problem at different scales\, phylogenetics focusing on relationships among species over long timescales\, and population genetics examining processes within species over shorter timescales. However\, the rapid growth of genome-scale data is blurring these boundaries and revealing increasingly complex\, non-treelike patterns of evolution driven by recombination\, gene flow\, and hybridization.   This workshop will bring together researchers from mathematics\, statistics\, and biology to explore the shared foundations of these fields and to develop new integrative approaches for modeling and inference. A particular focus will be on connections between ancestral recombination graphs and phylogenetic networks\, which\, despite arising in different contexts\, are mathematically equivalent structures used to represent reticulate evolutionary histories. ​  The program will emphasize collaboration and discussion\, featuring a tutorial day to establish common ground across disciplines\, followed by time for focused working group sessions as well as research presentations. Participants will identify key challenges\, compare modeling frameworks\, and initiate new research directions at the interface of stochastic processes\, graph theory\, and evolutionary biology.\n\nMore Info: https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop\n\nRegister: https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/phylogenetics-meets-population-genetics-workshop
CREATED:20260505T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260505T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:57
DTSTART;TZID=America/Chicago:20270517T083000
DTEND;TZID=America/Chicago:20270517T170000
DTSTAMP:20260622T090637Z
SUMMARY:Recent Advances and New Directions in Geometric Methods for Computational Biology and Medicine
UID:641408@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The concept of "shape" has taken an increasingly central place in the biomedical sciences. Historically\, the pioneering work of D'Arcy Thompson morphogenesis has introduced the idea of mathematical laws underlying the formation of patterns in plants\, animal and human anatomy. With the constant breakthroughs and innovations in biomedical imaging technologies\, and the resulting explosion in the availability of high-quality data\, the need for sound mathematical and computational models to analyze such data and uncover the underlying biological processes behind it has become all the more crucial. This led to the emergence of novel research areas\, such as\, in the late 1990s\, the field known as computational anatomy\, which aims at building models of the anatomical variability and developing quantitative approaches to extract morphological biomarkers associated to pathologies. On the mathematical side\, these questions have found natural connections with the construction of shape spaces and the problem of extending statistical methods to such spaces.  This workshop\, targeting a broad audience of mathematicians\, statisticians\, computational biologists and neuroscientists\, will be articulated around four main topics: latest developments in geometric frameworks for complex biological structures such as spatial networks and functional data\, longitudinal models of biological processes\, the rise of geometric deep learning and AI in biomedicine and finally the importance of community-maintained open-source softwares and datasets. \n\nMore Info: https://www.nitmb.org/geomethods-workshop\n\nRegister: https://www.nitmb.org/geomethods-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/geomethods-workshop
CREATED:20260406T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260406T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:58
DTSTART;TZID=America/Chicago:20270518T083000
DTEND;TZID=America/Chicago:20270518T170000
DTSTAMP:20260622T090637Z
SUMMARY:Recent Advances and New Directions in Geometric Methods for Computational Biology and Medicine
UID:641409@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The concept of "shape" has taken an increasingly central place in the biomedical sciences. Historically\, the pioneering work of D'Arcy Thompson morphogenesis has introduced the idea of mathematical laws underlying the formation of patterns in plants\, animal and human anatomy. With the constant breakthroughs and innovations in biomedical imaging technologies\, and the resulting explosion in the availability of high-quality data\, the need for sound mathematical and computational models to analyze such data and uncover the underlying biological processes behind it has become all the more crucial. This led to the emergence of novel research areas\, such as\, in the late 1990s\, the field known as computational anatomy\, which aims at building models of the anatomical variability and developing quantitative approaches to extract morphological biomarkers associated to pathologies. On the mathematical side\, these questions have found natural connections with the construction of shape spaces and the problem of extending statistical methods to such spaces.  This workshop\, targeting a broad audience of mathematicians\, statisticians\, computational biologists and neuroscientists\, will be articulated around four main topics: latest developments in geometric frameworks for complex biological structures such as spatial networks and functional data\, longitudinal models of biological processes\, the rise of geometric deep learning and AI in biomedicine and finally the importance of community-maintained open-source softwares and datasets. \n\nMore Info: https://www.nitmb.org/geomethods-workshop\n\nRegister: https://www.nitmb.org/geomethods-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/geomethods-workshop
CREATED:20260406T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260406T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:59
DTSTART;TZID=America/Chicago:20270519T083000
DTEND;TZID=America/Chicago:20270519T170000
DTSTAMP:20260622T090637Z
SUMMARY:Recent Advances and New Directions in Geometric Methods for Computational Biology and Medicine
UID:641410@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The concept of "shape" has taken an increasingly central place in the biomedical sciences. Historically\, the pioneering work of D'Arcy Thompson morphogenesis has introduced the idea of mathematical laws underlying the formation of patterns in plants\, animal and human anatomy. With the constant breakthroughs and innovations in biomedical imaging technologies\, and the resulting explosion in the availability of high-quality data\, the need for sound mathematical and computational models to analyze such data and uncover the underlying biological processes behind it has become all the more crucial. This led to the emergence of novel research areas\, such as\, in the late 1990s\, the field known as computational anatomy\, which aims at building models of the anatomical variability and developing quantitative approaches to extract morphological biomarkers associated to pathologies. On the mathematical side\, these questions have found natural connections with the construction of shape spaces and the problem of extending statistical methods to such spaces.  This workshop\, targeting a broad audience of mathematicians\, statisticians\, computational biologists and neuroscientists\, will be articulated around four main topics: latest developments in geometric frameworks for complex biological structures such as spatial networks and functional data\, longitudinal models of biological processes\, the rise of geometric deep learning and AI in biomedicine and finally the importance of community-maintained open-source softwares and datasets. \n\nMore Info: https://www.nitmb.org/geomethods-workshop\n\nRegister: https://www.nitmb.org/geomethods-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/geomethods-workshop
CREATED:20260406T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260406T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:60
DTSTART;TZID=America/Chicago:20270520T083000
DTEND;TZID=America/Chicago:20270520T170000
DTSTAMP:20260622T090637Z
SUMMARY:Recent Advances and New Directions in Geometric Methods for Computational Biology and Medicine
UID:641411@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The concept of "shape" has taken an increasingly central place in the biomedical sciences. Historically\, the pioneering work of D'Arcy Thompson morphogenesis has introduced the idea of mathematical laws underlying the formation of patterns in plants\, animal and human anatomy. With the constant breakthroughs and innovations in biomedical imaging technologies\, and the resulting explosion in the availability of high-quality data\, the need for sound mathematical and computational models to analyze such data and uncover the underlying biological processes behind it has become all the more crucial. This led to the emergence of novel research areas\, such as\, in the late 1990s\, the field known as computational anatomy\, which aims at building models of the anatomical variability and developing quantitative approaches to extract morphological biomarkers associated to pathologies. On the mathematical side\, these questions have found natural connections with the construction of shape spaces and the problem of extending statistical methods to such spaces.  This workshop\, targeting a broad audience of mathematicians\, statisticians\, computational biologists and neuroscientists\, will be articulated around four main topics: latest developments in geometric frameworks for complex biological structures such as spatial networks and functional data\, longitudinal models of biological processes\, the rise of geometric deep learning and AI in biomedicine and finally the importance of community-maintained open-source softwares and datasets. \n\nMore Info: https://www.nitmb.org/geomethods-workshop\n\nRegister: https://www.nitmb.org/geomethods-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/geomethods-workshop
CREATED:20260406T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260406T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:61
DTSTART;TZID=America/Chicago:20270521T083000
DTEND;TZID=America/Chicago:20270521T170000
DTSTAMP:20260622T090637Z
SUMMARY:Recent Advances and New Directions in Geometric Methods for Computational Biology and Medicine
UID:641412@northwestern.edu
TZID:America/Chicago
DESCRIPTION:The concept of "shape" has taken an increasingly central place in the biomedical sciences. Historically\, the pioneering work of D'Arcy Thompson morphogenesis has introduced the idea of mathematical laws underlying the formation of patterns in plants\, animal and human anatomy. With the constant breakthroughs and innovations in biomedical imaging technologies\, and the resulting explosion in the availability of high-quality data\, the need for sound mathematical and computational models to analyze such data and uncover the underlying biological processes behind it has become all the more crucial. This led to the emergence of novel research areas\, such as\, in the late 1990s\, the field known as computational anatomy\, which aims at building models of the anatomical variability and developing quantitative approaches to extract morphological biomarkers associated to pathologies. On the mathematical side\, these questions have found natural connections with the construction of shape spaces and the problem of extending statistical methods to such spaces.  This workshop\, targeting a broad audience of mathematicians\, statisticians\, computational biologists and neuroscientists\, will be articulated around four main topics: latest developments in geometric frameworks for complex biological structures such as spatial networks and functional data\, longitudinal models of biological processes\, the rise of geometric deep learning and AI in biomedicine and finally the importance of community-maintained open-source softwares and datasets. \n\nMore Info: https://www.nitmb.org/geomethods-workshop\n\nRegister: https://www.nitmb.org/geomethods-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/geomethods-workshop
CREATED:20260406T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260406T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:62
DTSTART;TZID=America/Chicago:20270614T083000
DTEND;TZID=America/Chicago:20270614T170000
DTSTAMP:20260622T090637Z
SUMMARY:Mathematical Modeling of Tumor-Immune Dynamics and Immunotherapies
UID:641063@northwestern.edu
TZID:America/Chicago
DESCRIPTION:This workshop is a collaboration between NITMB and the American Institute of Mathematics (AIM)   Mathematical modeling provides a powerful framework to integrate experimental data\, identify key mechanisms underlying the immune response\, and guide therapeutic strategies. This workshop\, sponsored by AIM\, will be devoted to developing and analyzing mathematical models that describe the complex interactions between tumors and the immune system\, with an emphasis on improving the design and efficacy of cancer immunotherapies. The goal is to bring together mathematicians\, biologists\, and clinicians to collaborate on problems at the interface of mathematics\, oncology\, and immunology. Participants will explore how mathematical analysis and computation can advance our understanding of tumor–immune dynamics across multiple spatial and temporal scales and inform the development of personalized cancer treatments.\n\nMore Info: https://www.nitmb.org/mathematical-modeling-of-tumor-immune-dynamics-and-immunotherapies
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/mathematical-modeling-of-tumor-immune-dynamics-and-immunotherapies
CREATED:20260327T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260327T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:63
DTSTART;TZID=America/Chicago:20270615T083000
DTEND;TZID=America/Chicago:20270615T170000
DTSTAMP:20260622T090637Z
SUMMARY:Mathematical Modeling of Tumor-Immune Dynamics and Immunotherapies
UID:641064@northwestern.edu
TZID:America/Chicago
DESCRIPTION:This workshop is a collaboration between NITMB and the American Institute of Mathematics (AIM)   Mathematical modeling provides a powerful framework to integrate experimental data\, identify key mechanisms underlying the immune response\, and guide therapeutic strategies. This workshop\, sponsored by AIM\, will be devoted to developing and analyzing mathematical models that describe the complex interactions between tumors and the immune system\, with an emphasis on improving the design and efficacy of cancer immunotherapies. The goal is to bring together mathematicians\, biologists\, and clinicians to collaborate on problems at the interface of mathematics\, oncology\, and immunology. Participants will explore how mathematical analysis and computation can advance our understanding of tumor–immune dynamics across multiple spatial and temporal scales and inform the development of personalized cancer treatments.\n\nMore Info: https://www.nitmb.org/mathematical-modeling-of-tumor-immune-dynamics-and-immunotherapies
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/mathematical-modeling-of-tumor-immune-dynamics-and-immunotherapies
CREATED:20260327T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260327T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:64
DTSTART;TZID=America/Chicago:20270616T083000
DTEND;TZID=America/Chicago:20270616T170000
DTSTAMP:20260622T090637Z
SUMMARY:Mathematical Modeling of Tumor-Immune Dynamics and Immunotherapies
UID:641065@northwestern.edu
TZID:America/Chicago
DESCRIPTION:This workshop is a collaboration between NITMB and the American Institute of Mathematics (AIM)   Mathematical modeling provides a powerful framework to integrate experimental data\, identify key mechanisms underlying the immune response\, and guide therapeutic strategies. This workshop\, sponsored by AIM\, will be devoted to developing and analyzing mathematical models that describe the complex interactions between tumors and the immune system\, with an emphasis on improving the design and efficacy of cancer immunotherapies. The goal is to bring together mathematicians\, biologists\, and clinicians to collaborate on problems at the interface of mathematics\, oncology\, and immunology. Participants will explore how mathematical analysis and computation can advance our understanding of tumor–immune dynamics across multiple spatial and temporal scales and inform the development of personalized cancer treatments.\n\nMore Info: https://www.nitmb.org/mathematical-modeling-of-tumor-immune-dynamics-and-immunotherapies
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/mathematical-modeling-of-tumor-immune-dynamics-and-immunotherapies
CREATED:20260327T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260327T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:65
DTSTART;TZID=America/Chicago:20270617T083000
DTEND;TZID=America/Chicago:20270617T170000
DTSTAMP:20260622T090637Z
SUMMARY:Mathematical Modeling of Tumor-Immune Dynamics and Immunotherapies
UID:641066@northwestern.edu
TZID:America/Chicago
DESCRIPTION:This workshop is a collaboration between NITMB and the American Institute of Mathematics (AIM)   Mathematical modeling provides a powerful framework to integrate experimental data\, identify key mechanisms underlying the immune response\, and guide therapeutic strategies. This workshop\, sponsored by AIM\, will be devoted to developing and analyzing mathematical models that describe the complex interactions between tumors and the immune system\, with an emphasis on improving the design and efficacy of cancer immunotherapies. The goal is to bring together mathematicians\, biologists\, and clinicians to collaborate on problems at the interface of mathematics\, oncology\, and immunology. Participants will explore how mathematical analysis and computation can advance our understanding of tumor–immune dynamics across multiple spatial and temporal scales and inform the development of personalized cancer treatments.\n\nMore Info: https://www.nitmb.org/mathematical-modeling-of-tumor-immune-dynamics-and-immunotherapies
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/mathematical-modeling-of-tumor-immune-dynamics-and-immunotherapies
CREATED:20260327T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260327T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:66
DTSTART;TZID=America/Chicago:20270618T083000
DTEND;TZID=America/Chicago:20270618T170000
DTSTAMP:20260622T090637Z
SUMMARY:Mathematical Modeling of Tumor-Immune Dynamics and Immunotherapies
UID:641067@northwestern.edu
TZID:America/Chicago
DESCRIPTION:This workshop is a collaboration between NITMB and the American Institute of Mathematics (AIM)   Mathematical modeling provides a powerful framework to integrate experimental data\, identify key mechanisms underlying the immune response\, and guide therapeutic strategies. This workshop\, sponsored by AIM\, will be devoted to developing and analyzing mathematical models that describe the complex interactions between tumors and the immune system\, with an emphasis on improving the design and efficacy of cancer immunotherapies. The goal is to bring together mathematicians\, biologists\, and clinicians to collaborate on problems at the interface of mathematics\, oncology\, and immunology. Participants will explore how mathematical analysis and computation can advance our understanding of tumor–immune dynamics across multiple spatial and temporal scales and inform the development of personalized cancer treatments.\n\nMore Info: https://www.nitmb.org/mathematical-modeling-of-tumor-immune-dynamics-and-immunotherapies
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:OPAQUE
URL:https://www.nitmb.org/mathematical-modeling-of-tumor-immune-dynamics-and-immunotherapies
CREATED:20260327T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260327T050000Z
PRIORITY:0
BEGIN:VALARM
TRIGGER:-PT10M
ACTION:DISPLAY
DESCRIPTION:Reminder
END:VALARM
END:VEVENT
BEGIN:VEVENT
SEQUENCE:67
DTSTART;VALUE=DATE:20270726
DTEND;VALUE=DATE:20270727
DTSTAMP:20260622T090637Z
SUMMARY:Computational Biofluids at PUIs: Building Collaborations and Sustainable Research Trajectories as Teacher-Scholars
UID:642252@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Computational biofluids research lies at the intersection of fluid mechanics\, applied mathematics\, scientific computing\, biology\, and physics\, and is increasingly shaped by data science\, artificial intelligence\, biomedical engineering\, and experimental methods. While this interdisciplinarity creates rich opportunities for discovery\, it also adds complexity particularly for faculty at primarily undergraduate institutions (PUIs). PUI faculty operate within demanding environments that include heavy teaching loads\, undergraduate-focused research mentoring\,  limited infrastructure\, and significant service commitments. These challenges are further intensified by constraints on grant writing\, fragmented research time\, and the need to balance disciplinary depth with interdisciplinary breadth.     This workshop is designed to support PUI researchers in computational biofluids by promoting practical\, sustainable strategies for conducting high-impact research. Through a collaborative and community-centered approach\, participants will explore interdisciplinary partnerships\, efficient research models\, and ways to reduce cognitive and mentoring load while maintaining rigorous scholarship. The workshop will foster connections among researchers in mathematics\, biology\, physics\, engineering\, data science\, and other disciplines. Participants will form working groups aimed at establishing new lines of inquiry including shared projects\, funding strategies\, student training\, and/or joint mentoring. It will also emphasize meaningful undergraduate  engagement\, including approaches to broaden participation among first-generation and underrepresented students. Participants will explore ways in which they could link experiments to theory or integrate emerging tools such as AI and data-driven methods into their teaching and/or research\, and discuss practical and ethical implications. Ultimately\, the workshop aims to empower PUI faculty to thrive as teacher–scholars by balancing research\, teaching\, and service\, while building a supportive interdisciplinary community that sustains productivity and innovation in computational biofluids research.\n\nMore Info: https://www.nitmb.org/computational-biofluids-at-puis-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/computational-biofluids-at-puis-workshop
CREATED:20260514T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260514T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:68
DTSTART;VALUE=DATE:20270727
DTEND;VALUE=DATE:20270728
DTSTAMP:20260622T090637Z
SUMMARY:Computational Biofluids at PUIs: Building Collaborations and Sustainable Research Trajectories as Teacher-Scholars
UID:642253@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Computational biofluids research lies at the intersection of fluid mechanics\, applied mathematics\, scientific computing\, biology\, and physics\, and is increasingly shaped by data science\, artificial intelligence\, biomedical engineering\, and experimental methods. While this interdisciplinarity creates rich opportunities for discovery\, it also adds complexity particularly for faculty at primarily undergraduate institutions (PUIs). PUI faculty operate within demanding environments that include heavy teaching loads\, undergraduate-focused research mentoring\,  limited infrastructure\, and significant service commitments. These challenges are further intensified by constraints on grant writing\, fragmented research time\, and the need to balance disciplinary depth with interdisciplinary breadth.     This workshop is designed to support PUI researchers in computational biofluids by promoting practical\, sustainable strategies for conducting high-impact research. Through a collaborative and community-centered approach\, participants will explore interdisciplinary partnerships\, efficient research models\, and ways to reduce cognitive and mentoring load while maintaining rigorous scholarship. The workshop will foster connections among researchers in mathematics\, biology\, physics\, engineering\, data science\, and other disciplines. Participants will form working groups aimed at establishing new lines of inquiry including shared projects\, funding strategies\, student training\, and/or joint mentoring. It will also emphasize meaningful undergraduate  engagement\, including approaches to broaden participation among first-generation and underrepresented students. Participants will explore ways in which they could link experiments to theory or integrate emerging tools such as AI and data-driven methods into their teaching and/or research\, and discuss practical and ethical implications. Ultimately\, the workshop aims to empower PUI faculty to thrive as teacher–scholars by balancing research\, teaching\, and service\, while building a supportive interdisciplinary community that sustains productivity and innovation in computational biofluids research.\n\nMore Info: https://www.nitmb.org/computational-biofluids-at-puis-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/computational-biofluids-at-puis-workshop
CREATED:20260514T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260514T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:69
DTSTART;VALUE=DATE:20270728
DTEND;VALUE=DATE:20270729
DTSTAMP:20260622T090637Z
SUMMARY:Computational Biofluids at PUIs: Building Collaborations and Sustainable Research Trajectories as Teacher-Scholars
UID:642254@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Computational biofluids research lies at the intersection of fluid mechanics\, applied mathematics\, scientific computing\, biology\, and physics\, and is increasingly shaped by data science\, artificial intelligence\, biomedical engineering\, and experimental methods. While this interdisciplinarity creates rich opportunities for discovery\, it also adds complexity particularly for faculty at primarily undergraduate institutions (PUIs). PUI faculty operate within demanding environments that include heavy teaching loads\, undergraduate-focused research mentoring\,  limited infrastructure\, and significant service commitments. These challenges are further intensified by constraints on grant writing\, fragmented research time\, and the need to balance disciplinary depth with interdisciplinary breadth.     This workshop is designed to support PUI researchers in computational biofluids by promoting practical\, sustainable strategies for conducting high-impact research. Through a collaborative and community-centered approach\, participants will explore interdisciplinary partnerships\, efficient research models\, and ways to reduce cognitive and mentoring load while maintaining rigorous scholarship. The workshop will foster connections among researchers in mathematics\, biology\, physics\, engineering\, data science\, and other disciplines. Participants will form working groups aimed at establishing new lines of inquiry including shared projects\, funding strategies\, student training\, and/or joint mentoring. It will also emphasize meaningful undergraduate  engagement\, including approaches to broaden participation among first-generation and underrepresented students. Participants will explore ways in which they could link experiments to theory or integrate emerging tools such as AI and data-driven methods into their teaching and/or research\, and discuss practical and ethical implications. Ultimately\, the workshop aims to empower PUI faculty to thrive as teacher–scholars by balancing research\, teaching\, and service\, while building a supportive interdisciplinary community that sustains productivity and innovation in computational biofluids research.\n\nMore Info: https://www.nitmb.org/computational-biofluids-at-puis-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/computational-biofluids-at-puis-workshop
CREATED:20260514T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260514T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:70
DTSTART;VALUE=DATE:20270729
DTEND;VALUE=DATE:20270730
DTSTAMP:20260622T090637Z
SUMMARY:Computational Biofluids at PUIs: Building Collaborations and Sustainable Research Trajectories as Teacher-Scholars
UID:642255@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Computational biofluids research lies at the intersection of fluid mechanics\, applied mathematics\, scientific computing\, biology\, and physics\, and is increasingly shaped by data science\, artificial intelligence\, biomedical engineering\, and experimental methods. While this interdisciplinarity creates rich opportunities for discovery\, it also adds complexity particularly for faculty at primarily undergraduate institutions (PUIs). PUI faculty operate within demanding environments that include heavy teaching loads\, undergraduate-focused research mentoring\,  limited infrastructure\, and significant service commitments. These challenges are further intensified by constraints on grant writing\, fragmented research time\, and the need to balance disciplinary depth with interdisciplinary breadth.     This workshop is designed to support PUI researchers in computational biofluids by promoting practical\, sustainable strategies for conducting high-impact research. Through a collaborative and community-centered approach\, participants will explore interdisciplinary partnerships\, efficient research models\, and ways to reduce cognitive and mentoring load while maintaining rigorous scholarship. The workshop will foster connections among researchers in mathematics\, biology\, physics\, engineering\, data science\, and other disciplines. Participants will form working groups aimed at establishing new lines of inquiry including shared projects\, funding strategies\, student training\, and/or joint mentoring. It will also emphasize meaningful undergraduate  engagement\, including approaches to broaden participation among first-generation and underrepresented students. Participants will explore ways in which they could link experiments to theory or integrate emerging tools such as AI and data-driven methods into their teaching and/or research\, and discuss practical and ethical implications. Ultimately\, the workshop aims to empower PUI faculty to thrive as teacher–scholars by balancing research\, teaching\, and service\, while building a supportive interdisciplinary community that sustains productivity and innovation in computational biofluids research.\n\nMore Info: https://www.nitmb.org/computational-biofluids-at-puis-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/computational-biofluids-at-puis-workshop
CREATED:20260514T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260514T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:71
DTSTART;VALUE=DATE:20270730
DTEND;VALUE=DATE:20270731
DTSTAMP:20260622T090637Z
SUMMARY:Computational Biofluids at PUIs: Building Collaborations and Sustainable Research Trajectories as Teacher-Scholars
UID:642256@northwestern.edu
TZID:America/Chicago
DESCRIPTION: Computational biofluids research lies at the intersection of fluid mechanics\, applied mathematics\, scientific computing\, biology\, and physics\, and is increasingly shaped by data science\, artificial intelligence\, biomedical engineering\, and experimental methods. While this interdisciplinarity creates rich opportunities for discovery\, it also adds complexity particularly for faculty at primarily undergraduate institutions (PUIs). PUI faculty operate within demanding environments that include heavy teaching loads\, undergraduate-focused research mentoring\,  limited infrastructure\, and significant service commitments. These challenges are further intensified by constraints on grant writing\, fragmented research time\, and the need to balance disciplinary depth with interdisciplinary breadth.     This workshop is designed to support PUI researchers in computational biofluids by promoting practical\, sustainable strategies for conducting high-impact research. Through a collaborative and community-centered approach\, participants will explore interdisciplinary partnerships\, efficient research models\, and ways to reduce cognitive and mentoring load while maintaining rigorous scholarship. The workshop will foster connections among researchers in mathematics\, biology\, physics\, engineering\, data science\, and other disciplines. Participants will form working groups aimed at establishing new lines of inquiry including shared projects\, funding strategies\, student training\, and/or joint mentoring. It will also emphasize meaningful undergraduate  engagement\, including approaches to broaden participation among first-generation and underrepresented students. Participants will explore ways in which they could link experiments to theory or integrate emerging tools such as AI and data-driven methods into their teaching and/or research\, and discuss practical and ethical implications. Ultimately\, the workshop aims to empower PUI faculty to thrive as teacher–scholars by balancing research\, teaching\, and service\, while building a supportive interdisciplinary community that sustains productivity and innovation in computational biofluids research.\n\nMore Info: https://www.nitmb.org/computational-biofluids-at-puis-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/computational-biofluids-at-puis-workshop
CREATED:20260514T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260514T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:72
DTSTART;VALUE=DATE:20271018
DTEND;VALUE=DATE:20271019
DTSTAMP:20260622T090637Z
SUMMARY:Collaborative Learning in Mathematical Biology (CLIMB) Workshop
UID:642653@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Biological systems are typically highly interconnected and complex. Mathematical biology often encompasses two extremes - an overwhelming amount of data or a dramatic paucity of data. In both cases\, mathematical formulations can be powerful tools allowing researchers to frame questions\, explore patterns\, and synthesize information. The interdisciplinary nature of mathematical biology requires a variety of skills. Facilitating interaction among research groups and institutions is important to move the discipline forward. This workshop continues the line of WIMB workshops previously held through IMA\, NIMBioS\, MBI\, IPAM\, and ICERM.   The CLIMB workshop aims to build research collaboration among researchers in mathematical biology\, with an emphasis on connecting early career researchers to more established mentors. The workshop collaboration groups are structured so that each has a senior researcher who presents a problem that the team collaborates on during the workshop and continues remotely after the workshop. Participants will spend the majority of the time at the workshop making significant progress on a research project and foster innovation in the application of mathematical\, statistical\, and computational methods in the resolution of significant problems in the biosciences with the goal of publishing research results in a collected volume. The workshop will also include career development lunchtime sessions.\n\nMore Info: https://www.nitmb.org/climb-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/climb-workshop
CREATED:20260527T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260527T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:73
DTSTART;VALUE=DATE:20271019
DTEND;VALUE=DATE:20271020
DTSTAMP:20260622T090637Z
SUMMARY:Collaborative Learning in Mathematical Biology (CLIMB) Workshop
UID:642654@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Biological systems are typically highly interconnected and complex. Mathematical biology often encompasses two extremes - an overwhelming amount of data or a dramatic paucity of data. In both cases\, mathematical formulations can be powerful tools allowing researchers to frame questions\, explore patterns\, and synthesize information. The interdisciplinary nature of mathematical biology requires a variety of skills. Facilitating interaction among research groups and institutions is important to move the discipline forward. This workshop continues the line of WIMB workshops previously held through IMA\, NIMBioS\, MBI\, IPAM\, and ICERM.   The CLIMB workshop aims to build research collaboration among researchers in mathematical biology\, with an emphasis on connecting early career researchers to more established mentors. The workshop collaboration groups are structured so that each has a senior researcher who presents a problem that the team collaborates on during the workshop and continues remotely after the workshop. Participants will spend the majority of the time at the workshop making significant progress on a research project and foster innovation in the application of mathematical\, statistical\, and computational methods in the resolution of significant problems in the biosciences with the goal of publishing research results in a collected volume. The workshop will also include career development lunchtime sessions.\n\nMore Info: https://www.nitmb.org/climb-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/climb-workshop
CREATED:20260527T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260527T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:74
DTSTART;VALUE=DATE:20271020
DTEND;VALUE=DATE:20271021
DTSTAMP:20260622T090637Z
SUMMARY:Collaborative Learning in Mathematical Biology (CLIMB) Workshop
UID:642655@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Biological systems are typically highly interconnected and complex. Mathematical biology often encompasses two extremes - an overwhelming amount of data or a dramatic paucity of data. In both cases\, mathematical formulations can be powerful tools allowing researchers to frame questions\, explore patterns\, and synthesize information. The interdisciplinary nature of mathematical biology requires a variety of skills. Facilitating interaction among research groups and institutions is important to move the discipline forward. This workshop continues the line of WIMB workshops previously held through IMA\, NIMBioS\, MBI\, IPAM\, and ICERM.   The CLIMB workshop aims to build research collaboration among researchers in mathematical biology\, with an emphasis on connecting early career researchers to more established mentors. The workshop collaboration groups are structured so that each has a senior researcher who presents a problem that the team collaborates on during the workshop and continues remotely after the workshop. Participants will spend the majority of the time at the workshop making significant progress on a research project and foster innovation in the application of mathematical\, statistical\, and computational methods in the resolution of significant problems in the biosciences with the goal of publishing research results in a collected volume. The workshop will also include career development lunchtime sessions.\n\nMore Info: https://www.nitmb.org/climb-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/climb-workshop
CREATED:20260527T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260527T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:75
DTSTART;VALUE=DATE:20271021
DTEND;VALUE=DATE:20271022
DTSTAMP:20260622T090637Z
SUMMARY:Collaborative Learning in Mathematical Biology (CLIMB) Workshop
UID:642656@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Biological systems are typically highly interconnected and complex. Mathematical biology often encompasses two extremes - an overwhelming amount of data or a dramatic paucity of data. In both cases\, mathematical formulations can be powerful tools allowing researchers to frame questions\, explore patterns\, and synthesize information. The interdisciplinary nature of mathematical biology requires a variety of skills. Facilitating interaction among research groups and institutions is important to move the discipline forward. This workshop continues the line of WIMB workshops previously held through IMA\, NIMBioS\, MBI\, IPAM\, and ICERM.   The CLIMB workshop aims to build research collaboration among researchers in mathematical biology\, with an emphasis on connecting early career researchers to more established mentors. The workshop collaboration groups are structured so that each has a senior researcher who presents a problem that the team collaborates on during the workshop and continues remotely after the workshop. Participants will spend the majority of the time at the workshop making significant progress on a research project and foster innovation in the application of mathematical\, statistical\, and computational methods in the resolution of significant problems in the biosciences with the goal of publishing research results in a collected volume. The workshop will also include career development lunchtime sessions.\n\nMore Info: https://www.nitmb.org/climb-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/climb-workshop
CREATED:20260527T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260527T050000Z
PRIORITY:0
END:VEVENT
BEGIN:VEVENT
SEQUENCE:76
DTSTART;VALUE=DATE:20271022
DTEND;VALUE=DATE:20271023
DTSTAMP:20260622T090637Z
SUMMARY:Collaborative Learning in Mathematical Biology (CLIMB) Workshop
UID:642657@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Biological systems are typically highly interconnected and complex. Mathematical biology often encompasses two extremes - an overwhelming amount of data or a dramatic paucity of data. In both cases\, mathematical formulations can be powerful tools allowing researchers to frame questions\, explore patterns\, and synthesize information. The interdisciplinary nature of mathematical biology requires a variety of skills. Facilitating interaction among research groups and institutions is important to move the discipline forward. This workshop continues the line of WIMB workshops previously held through IMA\, NIMBioS\, MBI\, IPAM\, and ICERM.   The CLIMB workshop aims to build research collaboration among researchers in mathematical biology\, with an emphasis on connecting early career researchers to more established mentors. The workshop collaboration groups are structured so that each has a senior researcher who presents a problem that the team collaborates on during the workshop and continues remotely after the workshop. Participants will spend the majority of the time at the workshop making significant progress on a research project and foster innovation in the application of mathematical\, statistical\, and computational methods in the resolution of significant problems in the biosciences with the goal of publishing research results in a collected volume. The workshop will also include career development lunchtime sessions.\n\nMore Info: https://www.nitmb.org/climb-workshop
LOCATION:Suite 3500\, Chicago\, IL 60611
TRANSP:TRANSPARENT
URL:https://www.nitmb.org/climb-workshop
CREATED:20260527T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260527T050000Z
PRIORITY:0
END:VEVENT
END:VCALENDAR