Hannah Choi

Hannah Choi is an Assistant Professor in the School of Mathematics at Georgia Tech's College of Sciences, where she leads a mathematical neuroscience research group. Her work bridges mathematics and neuroscience through computational modeling of brain networks.

Her research interests focus on mathematical approaches to neuroscience, specifically linking structures, dynamics, and computation in data-driven brain networks at multiple scales. She combines theoretical frameworks with data-driven models to understand how efficient and adaptable neural coding emerges from complex connectivity structure and rich neural dynamics in both biological and artificial neural networks. Her work spans computational neuroscience, mathematical modeling, brain network analysis, and neural dynamics with applications to artificial intelligence and representation learning.

Dr. Choi's recent publications demonstrate expertise in cortical microcircuit analysis, predictive coding, brain network synchronization, and neural computation. Her research group investigates diverse topics in computational and theoretical neuroscience through close collaboration with experimental groups.

• Patrick J McGovern Research Fellow

Her research is funded by the FLAP MURI project (Fast Lexicographic Agile Perception), investigating how flying insects integrate information from complex environments to develop perception frameworks. The group actively recruits postdocs and graduate students interested in mathematical neuroscience. Based in the School of Mathematics, her lab maintains strong connections with Bioengineering and Bioscience programs as an affiliated faculty member in Data Engineering and Science. The research group operates with a commitment to diversity, equity, and inclusion, acknowledging the Muscogee Creek and Cherokee peoples on whose ancestral lands Georgia Tech resides.