Mary Letey
Kempner Graduate Fellow
Ph.D. Student in Applied Mathematics
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About
Mary is a third year Ph.D. student in Applied Mathematics advised by Cengiz Pehlevan. Previously she studied and worked in theoretical physics at Cambridge University and Perimeter Institute.
Research Focus
Mary is interested in describing neural computation in the context of structured data and tasks, using tools from statistical physics and geometry. Her current work focuses on exact analysis of in-context learning using random matrix theory, and the effects of various data structures on learning. She also maintains an active interest in machine learning for scientific applications, especially the use of neural networks for solving PDEs and inverse problems.