Hannah Choi is an Assistant Professor in the School of Mathematics at Georgia Tech. Her research focuses on mathematical approaches to neuroscience, with primary interests in linking structures, dynamics, and computation in data-driven brain networks at multiple scales. 

She was previously a postdoctoral fellow at the University of Washington and also a visiting scientist at the Allen Institute for Brain Science, working with Eric Shea-Brown and Stefan Mihalas. Before coming to Georgia Tech, she was awarded an NIH BRAIN Initiative K99/R00 Pathway to Independence Award which funds the last 2 years of her postdoc at the University of Washington and the first 3 years as a faculty. 

During her postdoctoral training, she spent a semester (Spring 2018) at the Simons Institute for the Theory of Computing at the University of California, Berkeley, as a Simons Berkeley Research Fellow and Patrick J McGovern Research Fellow for the themed program The Brain and Computation. Before that, she was awarded a Washington Research Foundation Innovation Postdoctoral Fellowship in Neuroengineering to work with Eric Shea-Brown, Wyeth Bair and Anitha Pasupathy at the University of Washington.

She received her PhD in Applied Mathematics from Northwestern University, advised by Hermann Riecke and William Kath, and her BA in Applied Mathematics from the University of California, Berkeley.