PhD student · Computer Science · UC Santa Barbara
Hanning Zhang
I work on selective tool usage, efficient agent systems and agentic RL. Before that, I worked on LLM reasoning and alignment.
I'm a first-year PhD student at UC Santa Barbara, advised by Prof. Zhen Dong. I received my M.S. from UIUC working with Prof. Tong Zhang, and my B.S. from HKUST.
News
- Sep 2026 Started my PhD in Computer Science at UC Santa Barbara. 🎓
- 2026 Honored as a Siebel Scholar, Class of 2026. 🏅
- 2026 PhysProver accepted to Findings of EMNLP 2026.
- 2026 OpenGenAlign accepted to Findings of ACL 2026.
- Summer 2026 Applied Scientist Intern at Amazon, Palo Alto — multi-task & multi-domain learning for Ads.
- 2025 Gradient Variance Minimization (GVM) accepted to NeurIPS 2025; Entropy-Regularized PRM accepted to TMLR.
- 2025 ScaleBiO accepted to ACL 2025; Overadaptation in SFT accepted to ICML 2025.
- Summer 2025 Applied Scientist Intern at Amazon, Palo Alto — reward models for ML engineering.
Publications
* denotes equal contribution. Sorted roughly by recency.
Industry Experience
May – Aug 2026
Applied Scientist Intern, Amazon
Palo Alto, CA · Supervisor: Dr. Lin Zhong
Multi-task and multi-domain learning for Ads.
May – Aug 2025
Applied Scientist Intern, Amazon
Palo Alto, CA · Supervisor: Dr. Liang Qiu
Reward models for machine learning engineering.
Education
Sep 2026 –
University of California, Santa Barbara
PhD in Computer Science
Aug 2024 – May 2026
University of Illinois Urbana-Champaign
MS in Computer Science (thesis track)
Sep 2020 – Jun 2024
The Hong Kong University of Science and Technology
BS in Computer Science, First Class Honors
Selected Awards
- 🏅 Siebel Scholar, Class of 2026 ($35,000)
- 🏆 Outstanding Paper Award, NAACL 2024 (6 / 2434 ≈ 0.25%)