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When Is Partially Observable Reinforcement Learning Not Scary?

Statistical Guarantees for Link Prediction using Graph Neural Networks

Large Deviation Principles for Atypical Eigenvalues of Wigner Matrices

Large Deviations of the Largest Eigenvalue of a Deformed GOE Matrix with External Field

Wasserstein p Bounds for Degenerate U-Statistics

PhD

• Research Interests: Probability Theory, ML Theory, and High-Dimensional Statistics.

Undergraduate

• Thesis: Weak Solutions of the Fokker-Planck Equation Through Particle Systems Interacting Through Their Ranks