My name is Jingyan Shen. I am a first-year CS Ph.D. student at New York University (Courant Institute), advised by Prof. Matus Telgarsky and Prof. Pavel Izmailov. Previously, I earned my dual master degree from Tsinghua University and Columbia University. Prior to this, I completed my Bachelor’s degree at Wuhan University, majoring in Statistics.
I am broadly interested in machine learning and statistics, with a current focus on reinforcement learning for reasoning and planning. My current research studies when and why RL-based post-training improves reasoning in large language models. In particular, I am interested in:
- RL scaling and model priors: how the benefits and dynamics of RL post-training are shaped by what a model has already learned during pretraining or supervised fine-tuning.
- Weak-to-strong generalization: how RL can elicit stronger reasoning from limited, noisy, or weak supervision.
- Continual self-improvement: how LLMs can improve beyond fixed human-curated data through self-play, self-generated curricula, and verifier-guided exploration.
I am also fortunate to work with many great scholars and mentors, and I’m deeply grateful for their guidance.
🗞 News
- 2026.06: 🌃 Joining Microsoft Research (NYC) as a Research Intern in Summer 2026! Feel free to reach out if you would like to connect or chat about research!
- 2026.05: 🏅 Selected as an ICML 2026 Gold Reviewer.
- 2025.11: 🎉 MiCRo received the EMNLP 2025 Outstanding Paper Award!
🔬 Preprints & Workshops
(†: equal contribution)
When Can LLMs Learn to Reason with Weak Supervision?
Salman Rahman†, Jingyan Shen†, Anna Mordvina, Hamid Palangi, Saadia Gabriel, Pavel Izmailov
Preprint. [Paper] [Project Page]
When Reasoning Meets Its Laws
Junyu Zhang†, Yifan Sun†, Tianang Leng†, Jingyan Shen†, Ziyin Liu, Paul Pu Liang, Huan Zhang
Efficient Reasoning Workshop at NeurIPS 2025 (Oral Presentation, Best Paper Nomination) [Paper] [Website]
🔬 Selected Publications
Adversarially Robust Control of Conditional Value-at-Risk via Rockafellar-Uryasev Conformal Inference
Catherine Chen, Jingyan Shen, Zhun Deng, Lihua Lei
ICML 2026 [Paper]
MiCRo: Mixture Modeling and Context-aware Routing for Personalized Preference Learning
Jingyan Shen†, Jiarui Yao†, Rui Yang†, Yifan Sun, Feng Luo, Rui Pan, Tong Zhang, Han Zhao
EMNLP 2025 (Main) Outstanding Paper Award 🏆 [Paper]
Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay
Yifan Sun†, Jingyan Shen†, Yibin Wang†, Tianyu Chen, Zhendong Wang, Mingyuan Zhou, Huan Zhang
NeurIPS 2025 [Paper]
Conformal Tail Risk Control for Large Language Model Alignment
Catherine Chen, Jingyan Shen, Zhun Deng, Lihua Lei
ICML 2025 [Paper]
Rethinking Diverse Human Preference Learning through Principal Component Analysis
Feng Luo, Rui Yang, Hao Sun, Chunyuan Deng, Jiarui Yao, Jingyan Shen, Huan Zhang, Hanjie Chen
ACL 2025 (Findings) [Paper]
TimeInf: Time Series Data Contribution via Influence Functions
Yizi Zhang†, Jingyan Shen†, Xiaoxue Xiong†, Yongchan Kwon
ICLR 2025 [Paper] [Code]
2D-OOB: Attributing Data Contribution through Joint Valuation Framework
Yifan Sun†, Jingyan Shen†, Yongchan Kwon
NeurIPS 2024 [Paper] [Code]
🎖 Honors and Awards
- ICML 2026 Gold Reviewer, 2026
- Outstanding Paper Award, EMNLP 2025
- MacCracken Fellowship, New York University, 2025
- Outstanding Graduate Student (Top 1%), Tsinghua University, 2024
- Excellent Graduate Thesis Award, Tsinghua University, 2024
- Graduate Fellowship, Columbia University, 2023
- Outstanding Undergraduate Student, Wuhan University, 2021
- National Scholarship for Undergraduates, Ministry of Education of China, 2018
👾 Industry Experience
- 2024.02 - 2025.06, Full-time machine learning engineer at Pinterest
🐰 Miscs
I value the diversity and richness of life, and I hold a deep respect for beauty and purity in all their forms. Beyond research, I enjoy playing table tennis and tennis, playing drums, losing myself in a good book, or discovering new places through travel. My recent favorite books include Flowers for Algernon and Why Fish Don’t Exist. I am also a big fan of Stephen Sondheim’s musicals, particularly Company and Sunday in the Park with George. Born in Guangzhou, I’m picky about food and I particularly enjoy Japanese and Cantonese cuisine for their focus on fresh ingredients and natural flavors.
