Zaixi Zhang AI for Accelerating Invention (AI2) Postdoctoral Fellow Princeton AI Lab (AI2) Princeton University Princeton, NJ 08544 Email: zz8680@princeton.edu

My Photo

Biography

I am a Postdoctoral Fellow at the Princeton AI Lab (AI2), working under the mentorship of Prof. Mengdi Wang and Prof. Le Cong. My research focuses on AI for Science and Trustworthy AI. Prior to this, I completed my PhD at the University of Science and Technology of China (USTC), where I was advised by Prof. Qi Liu. During 2023-2024, I was co-advised by Prof. Marinka Zitnik from Harvard University. In 2019, I obtained my bachelor's degree from the School of the Gifted Young at USTC, majoring in Theoretical and Applied Mechanics. In 2021, I was a research intern at Tencent, mentored by Dr. Chee-Kong Lee. I have had the privilege of collaborating with Prof. Neil Gong, Prof. Earl Dowell, and Prof. Marinka Zitnik.

Research Statement in One Sentence: I build AI agents/Foundation Models/World Models to accelerate science discovery while ensuring safety and trustworthiness.

Featured Workshop Organization

NeurIPS 2025 Workshop: Biosecurity Safeguards for Generative AI
I am proud to serve as a core organizer of this pioneering workshop that addresses the critical intersection of AI innovation and biosecurity challenges. This workshop brings together leading experts in AI, synthetic biology, biosecurity policy, and ethics to develop actionable solutions for responsible AI development in life sciences.
Website: https://biosafe-gen-ai.github.io/
Date: December 2025, San Diego, California, USA
Mission: Engineering next-generation technical guardrails, establishing risk prediction benchmarks, and building a global coalition for secure AI innovation in biotechnology.

Representative Publications (Google Scholar, Code)

AI Agents for Science:
• STELLA: Self-Evolving LLM Agent for Biomedical Research [Code]
  Zaixi Zhang^✉, Ruofan Jin, Mengdi Wang, Le Cong
  arXiv, 2025.

• BioLab: End-to-End Autonomous Life Sciences Research with Multi-Agents System Integrating Biological Foundation Models
  Ruofan Jin, Yucheng Guo, Yuanhao Qu, Ming Yang, Chun Shang, Qirong Yang, Linlin Chao, Yi Zhou, Ruilai Xu, Ziyao Xu, Ruhong Zhou^✉, Zaixi Zhang^✉, Mengdi Wang^✉, Xiaoming Zhang^✉, Le Cong^✉
  under submission, 2025.

BioSafety and Biosecurity of Generative AI:
• Securing the Language of Life: Inheritable Watermarks from DNA Language Models to Proteins
  Zaixi Zhang, Ruofan Jin, Le Cong, Mengdi Wang
  NeurIPS, 2025.

• FoldMark: Protecting Protein Generative Models with Watermarking [Code] [Hugging Face]
  Zaixi Zhang, Ruofan Jin, Guangxue Xu, Xiaotong Wang, Marinka Zitnik, Le Cong, Mengdi Wang
  under submission, 2025.

• GeneBreaker: Jailbreak Attacks against DNA Language Models with Pathogenicity Guidance
  Zaixi Zhang, Zhenghong Zhou, Ruofan Jin, Le Cong, Mengdi Wang
  [Code] under submission, 2025.

• A Call for Built-in Biosecurity Safeguards for Generative AI Tools
  Mengdi Wang, Zaixi Zhang, Amrit Singh Bedi, Alvaro Velasquez, Stephanie Guerra, Sheng Lin-Gibson, Le Cong, Souradip Chakraborty, Megan Blewett, Yuanhao Qu, Jian Ma, Eric Xing, and George Church
  Nature Biotechnology, 2025.

AI for Science:
• RNAGenesis: Foundation Model for Enhanced RNA Sequence Generation and Structural Insights [Code] [Project]
  Zaixi Zhang, Ruofan Jin, Linlin Chao, Guangxue Xu, Yikun Zhang, Guowei Zhou, Di Yin, Yingqing Guo, Yaqi Fu, Yukang Yang, Kaixuan Huang, Xiaotong Wang, Junze Zhang, Yujie Yang, Qirong Yang, Ziyao Xu, E Weinan, Ruhong Zhou, Xiaoming Zhang, Mengdi Wang, Le Cong
  bioRxiv, 2025.

• ATOMICA: Learning Universal Representations of Intermolecular Interactions, [Code]
  Ada Fang, Zaixi Zhang, Andrew Zhou, Marinka Zitnik
  bioRxiv, 2025.

• A Systematic Survey in Geometric Deep Learning for Structure-based Drug Design, [Awesome-SBDD]
  Zaixi Zhang, Jiaxian Yan, Yining Huang, Qi Liu, Enhong Chen, Mengdi Wang, Marinka Zitnik
  ACM Computing Surveys, 2025.

• Efficient Generation of Protein Pockets with PocketGen, [Code]
  Zaixi Zhang, Wanxiang Shen, Qi Liu, Marinka Zitnik
  Nature Machine Intelligence, 2024.

• Generalized Protein Pocket Generation with Prior-Informed Flow Matching , [Code]
  Zaixi Zhang, Marinka Zitnik, Qi Liu
  The 38th Advances in Neural Information Processing Systems (NeurIPS (Spotlight)), 2024.
  

• FlexSBDD: Structure-Based Drug Design with Flexible Protein Modeling , [Code]
  Zaixi Zhang, Mengdi Wang, Qi Liu
  The 38th Advances in Neural Information Processing Systems (NeurIPS), 2024.
  

• DeltaDock: A Unified Framework for Accurate, Efficient, and Physically Reliable Molecular Docking , [Code]
  Jiaxian Yan, Zaixi Zhang, Jintao Zhu, Kai Zhang, Jianfeng Pei, Qi Liu
  The 38th Advances in Neural Information Processing Systems (NeurIPS), 2024.
  

• Full Atom Protein Pocket Design via Iterative Refinement, [Code]
  Zaixi Zhang, Zepu Lu, Zhongkai Hao, Marinka Zitnik, Qi Liu
  The 37th Advances in Neural Information Processing Systems (NeurIPS (Spotlight)), 2023.
  

• An Equivariant Generative Framework for Molecular Graph-Structure Co-Design, [Code]
  Zaixi Zhang, Qi Liu, Chee-Kong Lee, Chang-Yu Hsieh, Enhong Chen
  Chemical Science, 2023.

• Learning Subpocket Prototypes For Generalizable Structure Based Drug Design,
  Zaixi Zhang, Qi Liu
  The Fortieth International Conference on Machine Learning (ICML), 2023.
  

• Molecule Generation For Target Protein Binding with Structural Motifs, [Code]
  Zaixi Zhang, Yaosen Min, Shuxin Zheng, Qi Liu
  The Eleventh International Conference on Learning Representations (ICLR), 2023.
  

• Hierachical Graph Transformer with Adaptive Node Sampling, [Code]
  Zaixi Zhang, Qi Liu, Qingyong Hu, Chee-Kong Lee
  The 36th Advances in Neural Information Processing Systems (NeurIPS (Spotlight)), 2022.
  

• Graph Self-Supervised Learning for Optoelectronic Properties of Organic Semiconductors, [Code]
  Zaixi Zhang, Qi Liu, Shengyu Zhang, Chang-Yu Hsieh, Liang Shi, Chee-Kong Lee.
  Thirty-ninth International Conference on Machine Learning AI4Science Workshop, (ICML Workshop) 2022.
  

• Motif-based Graph Self-Supervised Learning for Molecular Property Prediction, [Code]
  Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Chee-Kong Lee
  The 35th Advances in Neural Information Processing Systems (NeurIPS), 2021.
  

Trustworthy AI:
• Backdoor Defense via Deconfounded Representation Learning, [Code]
  Zaixi Zhang, Qi Liu, Zhicai Wang, Zepu Lu, Qingyong Hu
  The IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
  

• FedRecover: Recovering from Poisoning Attacks in Federated Learning using Historical Information,
  Xiaoyu Cao, Jinyuan Jia, Zaixi Zhang, Neil Gong
  The 44th IEEE Symposium on Security and Privacy (IEEE S&P), 2023.
  

• FLCert: Provably Secure Federated Learning against Poisoning Attacks via Ensemble Methods,
  Xiaoyu Cao, Zaixi Zhang, Jinyuan Jia, Neil Gong
  IEEE Transactions on Information Forensics and Security (TIFS), 2022.

• Model Inversion Attacks Against Graph Neural Networks, [Code]
  Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chee-Kong Lee, Enhong Chen.
  Transactions on Knowledge and Data Engineering (TKDE), 2022.

• FLDetector: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clients, [Code]
  Zaixi Zhang, Xiaoyu Cao, Jinyuan Jia, Neil Gong
  The 28th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD), 2022.
  

• ProtGNN: Towards Self-Explaining Graph Neural Networks, [Code]
  Zaixi Zhang, Qi Liu, Hao Wang, Chengqiang Lu, Chee-Kong Lee
  The 36th AAAI Conference on Artificial Intelligence (AAAI), 2022.
  

• GraphMI: Extracting Private Graph Data from Graph Neural Networks, [Code]
  Zaixi Zhang, Qi Liu, Zhenya Huang, Hao Wang, Chengqiang Lu, Chuanren Liu, Enhong Chen
  The 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021.
  

• Backdoor attacks to graph neural networks, [Code]
  Zaixi Zhang, Jinyuan Jia, Binghui Wang, Neil Gong
  The 26th ACM Symposium on Access Control Models and Technologies (SACMAT), 2021.
  

Academic Services

Reviewer: Nature Methods, Nature Biotechnology, Nature Machine Intelligence.
AAAI, NeurIPS, ICML, ICLR, CVPR, ICCV, KDD, AISTATS, TKDE, TPAMI, TIFS, ACM Computing Surveys.

Talks

• Biosecurity in the Era of Bio Foundation Models: From Research Frontiers to FoldMark Innovations. Princeton BioE Lunch & Learn, March 15, 2025
• Generative AI for Drug Discovery. , Bilibili, November. 18, 2024

Honors & Awards

Chinese Academy of Sciences (CAS) President's Special Award (Highest Honor for PhD Graduates), 2024.

NSFC Doctoral Student Fellowship (Inaugural Cohort), 2023.

Best Presentation Award of 2021 Tencent Rhino-Bird Research Elite Program

Third Prize Scholarship of 2021 Tencent Rhino-Bird Research Elite Program (Top 6 of 62)

National Scholarship, 2021.

Tencent Excellent Intern (Top 5% Interns), 2021,2022,2024

Tencent Rhino Bird Talents Program, 2021.

Graduate Scholarship, Department of Computer Science and Engineering, University of Science and Technology of China, 2020.

Honorary graduate student of USTC (Top 5%), University of Science and Technology of China, 2019.

Excellent Student Scholarship, University of Science and Technology of China, 2016-2019.

Miscellany

Hobbies: Soccer, Swimming, PC Games, Hiking.

Global Visitors Map

Last Updated by Zaixi: September 20 2025