Zhepei Wei (魏哲培)/dʒɜːpeɪ/
Ph.D. Student·Computer Science Department·University of Virginia
About me
I am a CS Ph.D. student at the University of Virginia (UVA), advised by Prof. Yu Meng. I build efficient and self-improving agentic AI, from making LLMs cheaper to run (AdaDecode) and train (RELEX), to developing autonomous agents (WebAgent-R1) and systems that recursively improve themselves with no external supervision (Self-HPO). I have interned at 
Amazon, 
Meta, and 
Microsoft Research, and I am a recipient of the 
Capital One Ph.D. Fellowship.
On the job market. I'm open to both academic and industry positions starting in Spring/Fall 2027. Please feel free to reach out if interested!
What's New
[10/2026] Check out our latest work on self-evolving coding agents — “Self-HPO: Self-Evolving Coding Agents via Harness–Policy Optimization”!
[09/2026] Our paper “You Only Need Minimal RLVR Training: Extrapolating LLMs via Rank-1 Trajectories” is accepted at NeurIPS 2026.
[06/2026] Thrilled to receive the Capital One Ph.D. Fellowship!
[05/2026] Check out our latest work on RLVR training dynamics — “You Only Need Minimal RLVR Training: Extrapolating LLMs via Rank-1 Trajectories”!
[05/2026] Moved to Redmond and started my internship at Microsoft Research!
[04/2026] Our paper “TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning” is accepted at ICML 2026.
[04/2026] Our paper “Aligning Large Language Models via Fully Self-Synthetic Data” is accepted at ACL 2026.
[04/2026] Thrilled to receive the 2025-2026 UVA All-University Graduate Teaching Award (10 out of ~1,000 graduate TAs across UVA)!
[01/2026] Thrilled to receive the Tinker Research Grant from Thinking Machines ($5,000 credits)!
[10/2025] Check out our latest work on training truthful LLMs — “TruthRL: Incentivizing Truthful LLMs via Reinforcement Learning”!
[09/2025] Our paper “The Surprising Effectiveness of Negative Reinforcement in LLM Reasoning” is accepted at NeurIPS 2025.
[08/2025] Our paper “WebAgent-R1: Training Web Agents via End-to-End Multi-Turn Reinforcement Learning” is accepted at EMNLP 2025.
[05/2025] Thrilled to be selected as a top reviewer at ICML 2025!
[05/2025] Moved to Redmond and started my internship at Meta!
[05/2025] Check out our latest work on LLM-based web agents — “WebAgent-R1: Training Web Agents via End-to-End Multi-Turn Reinforcement Learning”!
[05/2025] Our paper “AdaDecode: Accelerating LLM Decoding with Adaptive Layer Parallelism” is accepted at ICML 2025.
[01/2025] Our paper “InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales” is accepted at ICLR 2025.
[01/2025] Moved to Seattle and started my internship at Amazon!
[09/2024] Thrilled to receive the Copenhaver Charitable Trust Bicentennial Fellowship ($12,000)!
[07/2024] Thrilled to be accepted to OpenAI's Researcher Access Program ($5,000 API credits)!
[06/2024] Check out our latest work on explicit denoising for RAG “InstructRAG: Instructing Retrieval-Augmented Generation via Self-Synthesized Rationales”!
[05/2024] Thrilled to be nominated for the Google PhD Fellowship (up to 3 nominees per university)!
[05/2024] Thrilled to receive the John A. Stankovic Outstanding Graduate Research Award!
[01/2024] Our paper “Incentivized Truthful Communication for Federated Bandits” is accepted at ICLR 2024.
[09/2023] Our paper “Incentivized Communication for Federated Bandits” is accepted at NeurIPS 2023.
[08/2022] Relocated to the lovely Charlottesville and began my Ph.D. journey at UVA!