I am a 4th-year PhD student of Machine Learning at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), supervised by Le Song. I also work closely with Eric Xing on FM4Bio projects. Prior to this, I received my master’s degree in Computer Science from University of Chinese Academy of Sciences (UCAS), supervised by Jiajun Zhang. During this time, I also worked closely with Chengqing Zong and Shaonan Wang on neural decoding of fMRI images. Before this, I received my bachelor’s degree in Statistics from Sun Yat-Sen University (SYSU).

Research Interests

I have broad research interests in applying AI to life sciences, with a particular focus on neuroscience and molecular biology. My current work centers on self-supervised learning, multimodal learning, with applications including:

• Developing large-scale biological foundation models for RNA and proteins.
• Predicting 3D structures of RNA and proteins.

I am open to collaborations and new opportunities!

Publications/Preprints

• Shuxian Zou, Jiayou Zhang, Bingkang Zhao, Hui Li, Eric P. Xing, Le Song. Accurate RNA 3D Structure Prediction via Language Model-Augmented AlphaFold 3. Accepted in Machine Learning in Structural Biology (MLSB), 2025. See you in EurIPS Copenhagen!
  • This project originated from our participation in the Stanford RNA 3D Folding competition — check out our Gold Medal solution.
• Caleb N. Ellington, Dian Li, Shuxian Zou, Elijah Cole, Ning Sun, Sohan Addagudi, Le Song, Eric P. Xing. Rapid and Reproducible Multimodal Biological Foundation Model Development with AIDO.ModelGenerator. In ICML 2025 Generative AI and Biology (GenBio) Workshop (Spotlight), ICML 2025 Workshop on Multi-modal Foundation Models and Large Language Models for Life Sciences (FM4LS).
  • [Github]
• Shuxian Zou, Tianhua Tao, Sazan Mahbub, Caleb Ellington, Robin Jonathan Algayres, Dian Li, Yonghao Zhuang, Hongyi Wang, Le Song, and Eric P. Xing. A large-scale foundation model for RNA function and structure prediction. In NeurIPS 2024 Workshop on AI for New Drug Modalities, 2024. (Spotlight)
  • [Github] [Hugging Face]
• Ning Sun, Shuxian Zou, Tianhua Tao, Sazan Mahbub, Dian Li, Yonghao Zhuang, Hongyi Wang, Xingyi Cheng, Le Song, and Eric P. Xing. Mixture of experts enable efficient and effective protein understanding and design. In NeurIPS 2024 Workshop on AI for New Drug Modalities, 2024. (Spotlight)
  • [Github] [Hugging Face]
• Shuxian Zou, Hui Li, Shentong Mo, Xingyi Cheng, Eric Xing, Le Song. Linker-Tuning: Optimizing Continuous Prompts for Heterodimeric Protein Prediction. arXiv preprint. Dec 2, 2023.
• Shuxian Zou, Shaonan Wang, Jiajun Zhang, and Chengqing Zong. Cross-Modal Cloze Task: A New Task to Brain-to-Word Decoding. In Findings of the Association for Computational Linguistics: ACL 2022, pages 648–657, Dublin, Ireland. Association for Computational Linguistics.
• Shuxian Zou, Shaonan Wang, Jiajun Zhang, Chengqing Zong. Towards Brain-to-Text Generation: Neural Decoding with Pre-trained Encoder-Decoder Models. In NeurIPS 2021 AI for Science Workshop. Online. Dec 13, 2021.