Alyson K.Fletcher
Helen Putnam Fellow
Understanding the Brain: Mathematics of Complex Networks

An assistant professor of statistics, electrical and computer engineering, computer science, and mathematics at UCLA, Alyson K. Fletcher develops algorithmic and mathematical methods toward understanding large-scale complex systems, with the broad goal of elucidating the neural basis of cognition and perception. Inspired by analogies with statistical physics, she is constructing a conceptual framework to infer global behavior from diverse slivers of information—essential in modelling and deciphering higher-level processes in the brain.

At the Radcliffe Institute, Fletcher is investigating the basic question of how sensory data is encoded in the neural cortex. New neural recording technologies, such as calcium imaging and high-dimensional electrocorticography now enable observations of neural activity at very fine resolution over large cortical areas. Fletcher is collaborating with leading experimental and systems neuroscientists, as well as experts in machine learning, to uncover fundamental structure and dynamics of cortical regions at multiple scales.

Fletcher obtained a BS degree in mathematics and physics from the University of Iowa and an MA degree in mathematics and MS and PhD degrees in electrical engineering from the University of California, Berkeley. Prior to joining UCLA, she was an assistant professor at UC Santa Cruz. She has been a University of California President’s Postdoctoral Fellow, a Henry Luce Foundation Claire Boothe Luce Fellow, and a recipient of a National Science Foundation Faculty Early Career Development Program (CAREER) award. She is a member of the founding steering committee of the Cognitive Computational Neuroscience conference.

2019–2020 Radcliffe Institute Fellows

This information is accurate as of the fellowship year indicated for each fellow.