Friday, July 31 2026 @ 12pm CT
Register at: https://tinyurl.com/3zhzu57j
Abstract
Biological tissues are incredibly complex with a range of diverse, dynamic, and heterogenous features. In order to provide the most holistic characterization of a biological tissue, we should strive to collect as much information as fast as possible. Of course, a variety of biological, logistical, and technological constraints limit what is feasible. Here, we explore this in the context of multimodal nonlinear optical microscopy, which can provide high resolution images with biochemical, metabolic, and structural contrast. Multimodal nonlinear optical microscopy traditionally has slow acquisition due to the need to collect multiple spectrally- and temporally-resolved images, many of which have unique excitation requirements. We can overcome this by incorporating computational methods into our image acquisition process to more efficiently collect only our target spectral, spatial, and temporal features of interest.
About Janet Sorrells
Janet E. Sorrells is the Donald L. Snyder Career Development Assistant Professor of Electrical & Systems Engineering at Washington University in St. Louis. Sorrells received her PhD in Bioengineering from the University of Illinois Urbana-Champaign in 2024 and subsequently started her lab at WashU, where she develops new techniques and applications for nonlinear optical microscopy. Sorrells has received numerous accolades for her work, including the 2023 JenLab Young Investigator Award, 2023 Illinois Innovation Award, 2024 Edmund Optics Ultrafast Educational Award, and most recently a 2025 NIH Director’s Early Independence Award.
Sponsored by the Center for Physical Genomics and Engineering, the Cancer and Physical Sciences Program at the Robert H. Lurie Comprehensive Cancer Center, and NIH Grants T32GM142604 and U54CA268084
Cost: Free, registration required at:
https://tinyurl.com/3zhzu57j