https://orcid.org/0000-0002-2559-8622
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 Duke 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
Pierre R. Lamond Department of Electrical and Computer Engineering,
Pratt School of Engineering
Assistant Professor of Computer Science
·
2023 - Present
Computer Science,
Trinity College of Arts & Sciences
Recent Scholarly Works
Inference-Time Alignment of Diffusion Models via Trust-Region Iterative Twisted Sequential Monte Carlo
Preprint · May 24, 2026 We study inference-time alignment for diffusion-based generative models, aiming to steer a base model toward high-reward outputs without updating its weights. Recent Sequential Monte Carlo (SMC)-based steering methods approximate reward-tilted target distr ... Link to item CiteCross-Domain Energy-Guided Diffusion Generation for Off-Dynamics Reinforcement Learning
Preprint · May 23, 2026 Off-dynamics offline reinforcement learning seeks to learn a target-domain policy from a large source dataset and a limited target dataset under mismatched transition dynamics. Existing approaches such as reward augmentation and data filtering are constrai ... Link to item CiteLocalized Dynamics-Aware Domain Adaption for Off-Dynamics Offline Reinforcement Learning
Preprint · February 24, 2026 Link to item CiteRecent Grants
CAREER: Harnessing the Power of Off-Dynamics Reinforcement Learning: Foundations, Algorithms, and Applications
ResearchPrincipal Investigator · Awarded by National Science Foundation · 2026 - 2031Collaborative 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
University of California, Los Angeles ·
2021
Ph.D.