Regular biography
SueYeon Chung is an Assistant Professor of Physics and of Applied Mathematics at Harvard University, affiliated with the Department of Physics. She is also an Institute Investigator at the Kempner Institute for the Study of Natural and Artificial Intelligence and the Center for Brain Science. Chung’s research investigates the fundamental principles of neural computation in biological and artificial neural networks, integrating concepts from statistical physics, machine learning, and neuroscience. Her work focuses on understanding how neural systems encode, transform, and process information through theoretical frameworks and ANN-based models. At Harvard, she explores topics at the intersection of physics, neuroscience, and AI, including neural representations, geometric structures of neural manifolds, and brain-inspired AI mechanisms.
Scholar-generated biography
SueYeon Chung is an Assistant Professor at Harvard University and the Flatiron Institute, specializing in Theoretical Neuroscience, Neural Networks, Neural Manifolds and Geometry, and Statistical Physics. Her research explores the geometric and statistical properties of neural populations, focusing on how biological and artificial neural networks represent and process information. Chung's work investigates the structure of object manifolds, generalization in deep learning, and the role of stochasticity in perception. Her publications highlight the interplay between neural geometry, efficient coding, and robustness in neural representations, contributing to both computational neuroscience and machine learning.