Assistant Professor at the Department of Computer Science, University of Illinois Chicago (UIC)
Member of the UIC CS Theory group and the IDEAL Institute
Primary research focus: developing, improving, and theoretically analyzing Reinforcement Learning with Human Feedback (RLHF) algorithms
Research areas: Machine Learning (especially Online Learning theory, Bandits, Reinforcement Learning), Optimization, Federated Learning, Differential Privacy, and Mechanism Design
Aims to build large-scale, robust, and intelligent AI models for sequential decision-making under partial or restricted feedback such as user interactions, preferences, demonstrations, proxy observations, and rankings