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Data-driven modeling, simulation and inference for neurobiological problems

Monday, September 28, 2026 | 8:30 AM - 5:00 PM CT
Suite 3500, Chicago, IL 60611

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.

Audience

  • Faculty/Staff
  • Student
  • Post Docs/Docs
  • Graduate Students

Contact

Tiffany Leighton
Email

Interest

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