Shenao Zhang

I am a first-year Ph.D. student at Northwestern University, advised by Prof. Zhaoran Wang. I am also a Student Researcher at Microsoft Research (MSR) working with Donghan Yu. I received my M.S. degree from Georgia Tech, where I was fortunate to work with Prof. Tuo Zhao and Prof. Bo Dai. I obtained my Bachelor's degree from South China University of Technology. In the spring of 2019, I visited UC Berkeley EECS. Previously, I was a research intern at ByteDance AML, MSR Asia, and Tencent AI Lab.

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Research

My research centers around Large Language Models (LLMs) and Reinforcement Learning (RL). I’m interested in developing autonomous agents and data-efficient decision-making algorithms/models with applications to robotic and multi-agent systems.

(* indicates equal contribution, ^† indicates equal advising)

How Can LLM Guide RL? A Value-Based Approach

Reason for Future, Act for Now: A Principled Framework for Autonomous LLM Agents with Provable Sample Efficiency

Model-Based Reparameterization Policy Gradient Methods: Theory and Practical Algorithms

Asking Before Action: Gather Information in Embodied Decision Making with Language Models

Maximize to Explore: One Objective Function Fusing Estimation, Planning, and Exploration

Adaptive Barrier Smoothing for First-Order Policy Gradient with Contact Dynamics

Conservative Dual Policy Optimization for Efficient Model-Based Reinforcement Learning

Learning Meta Representation for Agents in Multi-Agent Reinforcement Learning

Structure-Regularized Attention for Deformable Object Representation

Professional Service

Conference Review: NeurIPS 2020-23, ICLR 2022-23, AISTATS 2022-23, RSS 2021, ICML 2022-23.

Journal Review: Neurocomputing, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).

Teaching

Graduate Teaching Assistant: Head TA of CS 7648: Interactive Robot Learning (Fall 2021) at Georgia Tech.

Source code from Jon Barron's website