👋 Hi!

My name is Eric Jiang (姜汉晨), and I am an incoming Statistics and Data Science PhD student (25 Fall) at UCLA, supervised by Prof. Kai-Wei Chang and Prof. Yingnian Wu.

My research develops a comprehensive framework that integrates theoretical foundations in machine learning with practical applications in complex systems. By bridging the gap between advanced algorithms and domain-specific knowledge, I aim to build robust models that efficiently learn from data and make accurate predictions. My work focuses on enhancing reinforcement learning algorithms, improving the scalability of large models, and integrating uncertainty quantification into machine learning processes. Additionally, my current research is motivated by interdisciplinary projects in astrophysics, finance, and healthcare.

I am open to any research collaboration and internship 🥳! Feel free to contact me!

🔎 Current Research Topics

• Reinforcement Learning: Robust RL, offline/online RL, Maximum Entropy, Policy Sampling, In-Context Learning
• Large Language Models: Reinforcement Learning with Human Feedback (RLHF), Trustworthy, Safety
• Diffusion Models: Text-to-Image Stable Diffusion, Large Vision Langugage Model, Diffusion Sampling

🔥 News

• 2025.06:  🎉🎉 I graduated from University of California, Los Angeles with double degrees in Math of Computation and Statistics and Data Science
• 2025.01:  🎉🎉 I received the Graduate Dean’s Scholar Award (GDSA), awarded to the top 2 UCLA Statistics and Data Science PhD applicants (Top 1%).

📝 Publications

Preprint

CARES: Comprehensive Evaluation of Safety and Adversarial Robustness in Medical LLMs

Sijia Chen, Xiaomin Li, Mengxue Zhang, Eric Hanchen Jiang, Qingcheng Zeng, Chen-Hsiang Yu

Code

Preprint

Learning to Rank Chain-of-Thought: An Energy-Based Approach with Outcome Supervision

Eric Hanchen Jiang, Haozheng Luo, Shengyuan Pang, Xiaomin Li, Zhenting Qi, Hengli Li, Cheng-Fu Yang, Zongyu Lin, Xinfeng Li, Hao Xu, Kai-Wei Chang, Ying Nian Wu

Code

Preprint

Seek in the Dark: Reasoning via Test-Time Instance-Level Policy Gradient in Latent Space

Hengli Li, Chenxi Li, Tong Wu, Xuekai Zhu, Yuxuan Wang, Zhaoxin Yu, Eric Hanchen Jiang, Song-Chun Zhu, Zixia Jia, Ying Nian Wu, Zilong Zheng

Code

📖 Educations

• 2022.06 - 2025.06, University of California, Los Angeles (UCLA)
• 2021.09 - 2022.06, Southern University of Science and Technology (SUSTech)

🎖 Honors and Awards

• 2025.09 Awarded Graduate Dean’s Scholar Award (GDSA), Amount: $14,500.
• 2025.06 Awarded Cum Laude.