I am currently a 3th-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. Here is my CV.
My research focuses on generative modeling and optimization, with an emphasis on discrete diffusion models, reinforcement learning methods, and large language models. I am the author of Seq2Exp, a framework that leverages large language models to capture causal relationships between DNA and epigenomic data for gene-expression prediction, which was selected as an oral paper at ICLR 2025. I also proposed VIDD (Iterative Distillation for Reward-Guided Fine-Tuning of Diffusion Models in Biomolecular Design), which develops reinforcement learning to fine-tune discrete diffusion models.
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
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
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
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
Language Models for Controllable DNA Sequence Design
Xingyu Su*, Haiyang Yu*, Degui Zhi, Shuiwang Ji
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
International Conference on Learning Representations (ICLR) 2026
Neural Information Processing Systems (NeurIPS) 2025
The Conference on Information and Knowledge Management (CIKM) 2025,2024
Here is my CV[PDF].