I am a Senior Researcher in Tencent AI (Seattle). My primary research interest lies in natural language processing and machine learning. My current focus is building self-improving LLMs that can continuously learn from interaction, feedback, and experience. To support this goal, I have extensively studied and applied reinforcement learning (RL) for post-training, reasoning, and agentic behaviors in large-scale models.

I earned my Ph.D. in Computer Science and Engineering from the University of Notre Dame in 2023, advised by Prof. Meng Jiang. My research during Ph.D was generously supported by Bloomberg Ph.D Fellowship. I also enjoyed some amazing internship experiences at Microsoft Research, Allen Institute for Artificial Intelligence (AI2), and Bloomberg along the way.

What’s New!

- Check my latest post on X (Twitter)!
- [2026.01] Four papers have been accepted at ICLR 2026, covering topics of self-improving LLMs and parallel reasoning.
- [2025.08] One paper has been accepted at EMNLP 2025 on self-evolving agent.

Internship with Me

I am actively seeking highly motivated interns who share my research interests. Kindly reach out to me at wenhaoyu97@gmail.com / wenhaowyu@global.tencent.com with your resume!

I’ve been fortunate to mentor and work alongside many talented students:
- Chengsong Huang (2024), WUSTL, advised by Prof. Jiaxin Huang. Topic: Self-improving LLM [R-Zero].
- Shangbin Feng (2024), UW at Seattle, advised by Prof. Yulia Tsvetkov. Topic: Multi-Agent [SwitcherLM].
- Zongxia Li (2025), UMD, advised by Prof. Jordan Boyd-Graber. Topic: Self-improving LLM [Vision-SR1].
- Siru Ouyang (2024), UIUC, advised by Prof. Jiawei Han. Topic: LLM agent [RepoGraph].
- Mengzhao Jia (2024), UND, advised by Prof. Meng Jiang. Topic: Multi-modal [Leopard].
- Tong Chen (2023), UW at Seattle, advised by Prof. Luke Zettlemoyer and Prof. Hannaneh Hajishirzi. Topic: RAG [Dense X Retrieval].