Bing Wen Brunton.

Bing Wen Brunton

Professor of biology
University of Washington

Bing Wen Brunton is professor of biology and Richard and Joan Komen University Chair at the University of Washington, with affiliations at the eScience Institute for Data Science, the Paul G. Allen School of Computer Science and Engineering, and the Department of Applied Mathematics. She is a computational neuroscientist with a particular interest in natural behavior. She studies how the nervous system solves challenges that are vital to the animal: sensing the environment, maneuvering in the physical world, planning and executing goals, and interacting with their societies. Her research group develops data-intensive methods to build models of the nervous system and body using approaches from dynamical systems and control, deep reinforcement learning, computer vision, and physics-constrained simulations. Her YouTube channel @bingsbrain has video lectures on neuroscience and data science, and occasionally features original watercolor art.

Brunton earned her B.S. in biology at the California Institute of Technology and her Ph.D. in neuroscience from Princeton University, working with Carlos Brody.

Explore more from The Transmitter

Grace Hwang and Joe Monaco discuss the future of NeuroAI

Hwang and Monaco organized a recent workshop to hear from leaders in the field about how best to integrate NeuroAI research into the BRAIN Initiative.

By Paul Middlebrooks
4 December 2024 | 97 min listen
Illustration of a person holding a box that is emitting laser-like beams and projecting a large curved black surface.

Imagining the ultimate systems neuroscience paper

A growing body of papers on systems neuroscience and on giant simulations of neural circuits involves data beyond the point that anyone can reasonably understand end to end. Looking ahead, “paper-bots” could solve that problem.

By Mark Humphries
2 December 2024 | 8 min read

Hessameddin Akhlaghpour outlines how RNA may implement universal computation

Could the brain’s computational abilities extend beyond neural networks to molecular mechanisms? Akhlaghpour describes how natural universal computation may have evolved via RNA mechanisms.

By Paul Middlebrooks
26 November 2024 | 107 min listen