Icahn School of Medicine, Friedman Brain Institute
Student Researcher | July 2024 - Present
Theory (Jul 2024–Aug 2025). Co-authored a theory paper using random-matrix and concentration-of-measure tools to study how high-dimensional population codes evolve while preserving core geometric structure. The work formalizes conditions under which large-scale representational structure remains stable despite neuron-level turnover and specifies testable signatures of organized drift.
Current collaboration (Aug 2025 - Present) In collaboration with the Denise Cai lab, I lead the computational analysis of longitudinal CA1 miniscope recordings from mice performing a spatial navigation task to characterize the organization of cognitive maps.
-
What remains invariant across days and contexts in spatial memory representations?
-
What changes, and in what form, for example structured transformations versus wholesale reorganization?
-
On what timescales do these changes unfold?
-
What aspects of function are preserved across sessions, for example place-relevant structure?
And many more questions…
New York University, Courant Institute of Mathematical Sciences
Student Researcher | May 2024 - Jan 2025
Conducted research on Krylov subspace methods and their application to machine learning regularization under Dr. Tyler Chen. Optimized the Conjugate Gradient method with randomized algorithms and preconditioning techniques. Implemented the Nyström method in Python, evaluating accuracy, speed, and scalability across models to improve solutions for large-scale machine learning problems in high-dimensional settings.