Overview
My research is centered around Machine Learning, with broad interests in the areas of Artificial Intelligence, Data Science, Optimization, Reinforcement Learning, High Dimensional Statistics, and their applications to real-world problems including Bioinformatics and Healthcare. My research goal is to develop computationally- and data-efficient machine learning algorithms with both strong empirical performance and theoretical guarantees.
Current Appointments & Affiliations
Assistant Professor of Biostatistics & Bioinformatics
·
2022 - Present
Biostatistics & Bioinformatics, Division of Translational Biomedical,
Biostatistics & Bioinformatics
Assistant Professor in the Department of Electrical and Computer Engineering
·
2022 - Present
Electrical and Computer Engineering,
Pratt School of Engineering
Assistant Professor of Computer Science
·
2023 - Present
Computer Science,
Trinity College of Arts & Sciences
Recent Publications
How to Provably Improve Return Conditioned Supervised Learning?
Preprint · June 10, 2025 Link to item CiteLinear Mixture Distributionally Robust Markov Decision Processes
Preprint · May 23, 2025 Link to item CiteRobust Offline Reinforcement Learning with Linearly Structured $f$-Divergence Regularization
Preprint · November 27, 2024 Link to item CiteRecent Grants
Collaborative Research: Towards the Foundation of Approximate Sampling-Based Exploration in Sequential Decision Making
ResearchPrincipal Investigator · Awarded by National Science Foundation · 2023 - 2026View All Grants
Education, Training & Certifications
University of California, Los Angeles ·
2021
Ph.D.