Research Interests
Neural network models have revolutionized artificial intelligence, yet the mathematical foundations of their success remain unclear. My research investigates the learning dynamics of neural networks to understand how inductive biases emerge through training and how networks extract meaningful representations from data. Integrating insights from statistics, physics, and neuroscience, I aim to uncover fundamental mathematical principles governing learning in both artificial and natural intelligence.
