Han (Felix) Yan

Hi, I am Han (Felix) Yan (严涵), a fourth year undergraduate student studying at the The Chinese University of Hong Kong, Shenzhen. I'm an incoming CS PhD student at New York University (NYU) Courant Institute School of Mathematics, Computing, and Data Science in Fall 2026. I was also an exchange student at the University of Notre Dame. I am fortunated to be advised by Prof. Jianwei Huang at the NCEL lab, Prof. Meng Jiang at the DM2 lab and Prof. Benyou Wang at the CUHKSZ Freedom AI lab.

My research interest lies in GenAI (e.g. MLLM/LLM/) Safety, AI Privacy, Trustworthy AI, CoT, Reinforcement Learning Reward Model and etc. Currently, I am exploring CoT and RL Reward Model Design.

Please feel free to drop me an Email for any form of communication or collaboration!

Email  /  Google Scholar  /  Github  /  LinkedIn  / 

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🔥What's New
  • 2026/05/26 One co-first author paper is out on arxiv! Link here: HiMed
  • 2026/05/15 Our survey "Inference-Time Control for Trustworthy Large Language Models" is now available on Preprints.org!
  • 2026/04/15 I will start my PhD study at New York University Courant! Many thanks for all the help along the way.
  • 2026/01/26 One first-author paper got accepted by ICLR 2026! Link here: PRISM
  • 2025/09/29 One first-author paper is out on arxiv! Link here: PRISM
Publications (* indicates equal contribution)
2026
himed HiMed: Incentivizing Hindi Reasoning in Medical LLMs
Dingfeng Jiang*, Han Yan*, Chenze Ma*, Amit Kumar Jaiswal*, Ang Li, Yunxiang Jiang, Xinlei Xiong, Juhao Liang, Hongru Xiao, Xiang Li, Fan Bu, Jiale Han, Ruchir Gupta, Prayag Tiwari, Benyou Wang
arxiv Preprint.

We introduce HiMed, a Hindi reasoning medical corpus and benchmark suite covering both Western and Indian medicine. We further propose HiMed-8B, a Hindi-form medical reasoning LLM, through the design of decaying scaffolding reward. Extensive experiments demonstrate improvement in Hindi medical reasoning performance and reduction in the English--Hindi accuracy gap. Ablation studies validate the contribution of each training stage and reward component.

survey Inference-Time Control for Trustworthy Large Language Models: A Survey
Yuyang Bai*, Zheyuan Liu*, Han Yan, Zhangchen Xu, Yixin Wan, Canyu Chen, Zehong Wang, Xiangchi Yuan, Yue Huang, Guangyao Dou, Yuji Zhang, Hangxiao Zhu, Zhuofeng Li, Manling Li, Xiangliang Zhang, Mohit Bansal, Sanmi Koyejo, Kai-Wei Chang, Yu Zhang, Meng Jiang
Preprints.org, 2026.
website / code / pdf

A comprehensive survey of inference-time control techniques for trustworthy LLMs. We organize methods into four families — guardrails, internal-representation steering, multi-agent verification, and evaluation — and analyze open challenges across reliability, safety, fairness, privacy, and explainability.

2025
PRISM Dual-Space Smoothness for Robust and Balanced LLM Unlearning
Han Yan*, Zheyuan Liu*, Meng Jiang
ICLR 2026.

We propose a unified framework that enforces dual-space smoothness in representation and parameter spaces to improve robustness and balance unlearning metrics.

Synthetic Power Network Topology Generation with Geographical Information Synthetic Power Network Topology Generation with Geographical Information
Yulin Song, Han Yan, Chenxi Sun, Jianwei Huang
Proceedings of ACM E-Energy 2025.

We propose an approach that diversifies grid representations and includes a rigorous evaluation process using multi-modal large language models (MLLMs) to ensure output consistency.

2024
SCEMS An LLM-Assisted Framework for Synthetic Power Network Graph Generation
Yulin Song, Han Yan, Chenxi Sun, Jianwei Huang
SCEMS 2024 (Best Oral Paper).

We propose a large language model-assisted workflow for small-scale synthetic power grid generation, verification, and visualization.

Industrial Experience
Image Baidu, Inc.
Pudong, Shanghai, CN
2025.08 - 2025.09

Algorithm Engineering Intern @ Xiaodu
Image Shenzhen Institute of Artificial Intelligence and Robotics for Society
Shenzhen, Guangdong, CN
2024.09 - 2024.10

Research Intern
Advisor: Dr. Chenxi Sun
Education
Image New York University
New York City, NY, USA
2026.09 -

Ph.D. in Computer Science
Advisor: Prof. Qiaoyu Tan
Image University of Notre Dame
South Bend, IN, USA
2025.01 - 2025.07

Exchange Student & Summer Research
Advisor: Prof. Meng Jiang
Image The Chinese University of Hong Kong, Shenzhen
Shenzhen, Guangdong, CN
2022.09 - 2026.05 (Expected)

B.E. in Computer Science
Miscellaneous
  • I've always been surrounded by wonderful friends, collaborators, and advisors, and I try to maintain an optimistic outlook. If you're having a tough time and would like someone to talk to, feel free to reach out!
  • I like pop music and reading science fiction. The Three-Body Problem is my favorite science fiction series.
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