I am a 4th-year PhD student in Machine Learning at Mohamed bin Zayed University of Artificial Intelligence (MBZUAI), supervised by Prof. Le Song, and I work closely with Prof. Eric Xing on FM4Bio projects. I completed my master’s degree in Computer Science at University of Chinese Academy of Sciences (UCAS) and Institute of Automation, Chinese Academy of Sciences, where I worked with Prof. Chengqing Zong, Prof. Jiajun Zhang, and Dr. Shaonan Wang on neural decoding of fMRI images.

Before entering graduate school, I spent four years working as a data analyst at China Mobile. I received my bachelor’s degree in Statistics from Sun Yat-Sen University (SYSU).

Research Interests

I am passionate about applying AI to the life sciences, particularly in 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!

Preprints

• Youhan Lee, Shujun He, Toshiyuki Oda, …, Shuxian Zou, …, David Baker, …, Rhiju Das. Template-based RNA structure prediction advanced through a blind code competition. bioRxiv preprint. Dec 30, 2025. [Paper]
• Shuxian Zou, Jiayou Zhang, Bingkang Zhao, Hui Li, Eric P. Xing, Le Song. Improving RNA 3D Structure Prediction via Language Model-Augmented AlphaFold 3. Accepted in Machine Learning in Structural Biology (MLSB) workshop 2025, EurIPS Copenhagen. [Paper]
• 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). [Paper] [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) [Paper] [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) [Paper] [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. [Paper]

Publications

• 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. [Paper] [Github]
• 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. [Paper]

Competitions

• Stanford RNA 3D Folding (Kaggle, 2025) — 6th place out of 1,516 teams (Gold Medal).
  • Team: Littletree🎄 & Moth & Bianco.
  • Contributors: Shuxian Zou, Alejo Paullier, Bingkang Zhao.
  • My contributions: Augment Protenix with AIDO.RNA embeddings to improve RNA 3D structure prediction.
  • Solution write-up
• The 3rd Magic Mirror Cup – Intelligent Customer Service Question Similarity Algorithm Design (2018) - 16th out of 359 teams in the first round; 12th out of 95 teams in the final round.
  • Team: moka_tree.
  • Contributors: Lei Zhu, Shuxian Zou.
  • My contributions: Solution write-up (Chinese), Github