About

I am a Ph.D. student at Purdue University’s Machine Intelligence and Networked Data Science Group (MINDS) Laboratory advised by Prof. Abolfazl Hashemi.

My research interests lie at the intersection of stochastic optimization and trustworthy deep learning. I am particularly interested in developing optimization methods for nonconvex learning under realistic assumptions, with theoretical convergence guarantees that better reflect modern deep learning settings. I also study the generalization of and variance reduction for deep neural networks, with a focus on improving data efficiency and enhancing robustness under distribution shifts.

Research Interests

• Optimization (Constrained/Unconstrained Optimization Theory, Multi-Objective Optimization)
• Trustworthy Deep Learning (Robustness, Privacy, Memorization)
• Distributionally Robust Optimization (Invariant Learning, Subpopulation Shift, Domain Generalization)