I am currently a 4th-year Ph.D. student in the Department of Computer Science & Engineering, Texas A&M University. My advisor is Prof. Shuiwang Ji, who leads the Data Integration, Visualization, and Exploration (DIVE) Laboratory . I obtained my Master’s and Bachelor’s degrees from Shanghai Jiao Tong University in 2023 and 2020, respectively.
My research focuses on LLM post-training, with an emphasis on reinforcement learning, on-policy distillation, and inference-time scaling.
From Self-Distillation to Self-Practice: Privileged Information for Multi-Turn Agents
Xingyu Su, Abhishek Kumar, Qing Ping, Youzhi Luo, Jonathan Buck, Zach Zhang, Subramanian Chidambaram, Vinayak Arannil
arXiv, 2026
Data-Efficient Autoregressive-to-Diffusion Language Models via On-Policy Distillation
Xingyu Su*, Jacob Helwig*, Shubham Parashar*, Atharv Chagi, Lakshmi Jotsna, Degui Zhi, James Caverlee, Dileep Kalathil, Shuiwang Ji
arXiv, 2026
A Joint Diffusion Model with Pre-Trained Priors for RNA Sequence–Structure Co-Design
Xiner Li, Masatoshi Uehara, Xingyu Su, Gabriele Scalia, Shuiwang Ji
International Conference on Learning Representations (ICLR), 2026
Generative Artificial Intelligence for Biology: Toward Unifying Models, Algorithms, and Modalities
Xiner Li*, Xingyu Su*, Yuchao Lin, Chenyu Wang, Yijia Xiao, Tianyu Liu, Chi Han, Michael Sun, Montgomery Bohde, Anna Hart, Wendi Yu, Masatoshi Uehara, Gabriele Scalia, Xiao Luo, Carl Edwards, Wengong Jin, Jianwen Xie, Ehsan Hajiramezanali, Edward De Brouwer, Qing Sun, Byung-Jun Yoon, Xiaoning Qian, Marinka Zitnik, Heng Ji, Hongyu Zhao, Wei Wang, Shuiwang Ji
ChemRxiv, 2026
Autonomous Agents for Scientific Discovery: Orchestrating Scientists, Language, Code, and Physics
Lianhao Zhou, Hongyi Ling, Cong Fu, Yepeng Huang, Michael Sun, Wendi Yu, Xiaoxuan Wang, Xiner Li, Xingyu Su, Junkai Zhang, Xiusi Chen, Chenxing Liang, Xiaofeng Qian, Heng Ji, Wei Wang, Marinka Zitnik, Shuiwang Ji
arXiv, 2025
Iterative Distillation for Reward-Guided Fine-Tuning of Diffusion Models in Biomolecular Design
Xingyu Su*, Xiner Li*, Masatoshi Uehara*, Sunwoo Kim, Yulai Zhao, Gabriele Scalia, Ehsan Hajiramezanali, Tommaso Biancalani, Degui Zhi, Shuiwang Ji
International Conference on Learning Representations (ICLR), 2026
Dynamic Search for Inference-Time Alignment in Diffusion Models
Xiner Li*, Masatoshi Uehara*, Xingyu Su, Gabriele Scalia, Tommaso Biancalani, Aviv Regev, Sergey Levine, Shuiwang Ji
arXiv, 2025
Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design
Masatoshi Uehara*, Xingyu Su*, Yulai Zhao, Xiner Li, Aviv Regev, Shuiwang Ji, Sergey Levine, Tommaso Biancalani
International Conference on Machine Learning (ICML), 2025
Learning to Discover Regulatory Elements for Gene Expression Prediction
Xingyu Su*, Haiyang Yu*, Degui Zhi, Shuiwang Ji
International Conference on Learning Representations (ICLR Oral), 2025
Language Models for Controllable DNA Sequence Design
Xingyu Su, Xiner Li, Yuchao Lin, Ziqian Xie, Degui Zhi, Shuiwang Ji
Transactions on Machine Learning Research (TMLR), 2025
AAAI Conference on Artificial Intelligence (AAAI) 2027
International Conference on Machine Learning (ICML) 2026
Neural Information Processing Systems (NeurIPS) 2026,2025
International Conference on Learning Representations (ICLR) 2026
The Conference on Information and Knowledge Management (CIKM) 2025,2024