Kaiyuan Zhang Kaiyuan Zhang
How to pronounce?

PhD candidate
Purdue University
Office: 305 N. University Street
West Lafayette, IN, 47907-2107
Email: [email protected]
Google Scholar | dblp | Twitter | GitHub | LinkedIn

I am a PhD candidate of Computer Science at Purdue University, co-advised by Prof. Ninghui Li and Prof. Xiangyu Zhang. I am supported by the Amazon Fellowship. My research interests focus on security and privacy in machine learning, recently in safe & responsible large language models.

I was a research intern at Amazon AWS GenAI and NEC Labs America during my PhD. Before joining Purdue, I spent a wonderful year as a visiting graduate student at the University of Illinois at Urbana-Champaign, co-advised by Prof. Tao Xie and Prof. Tianyin Xu. I received an M.S. in Computer Science from the University of Texas at Dallas, advised by Prof. Wei Yang. I was a full-time research assistant advised by Prof. Wei Chen for 1.5 years at Zhejiang University before starting grad school.

Research Opportunities: I am always happy to discuss and brainstorm; if you’re a researcher/student interested in privacy, security, or AI safety (LLMs most recent), please reach out to [email protected].

Office Hours: I owe a lot to my patient research mentors who generously spent their time helping me along the way. From Sept. 2024, I will dedicate 2 hours each week to offer mentorship to undergrad and grad students on any topics you’d like to discuss. If you’re interested, please fill out the AMA form.

Selected Works [Full List] [Google Scholar] [dblp] (*: equal contribution)

  • μKE: Matryoshka Unstructured Knowledge Editing of Large Language Models
    Zian Su*, Ziyang Huang*, Kaiyuan Zhang, Xiangyu Zhang
    Preprint 2025
    [paper] [code (coming soon)]
  • CENSOR: Defense Against Gradient Inversion via Orthogonal Subspace Bayesian Sampling
    Kaiyuan Zhang, Siyuan Cheng, Guangyu Shen, Bruno Ribeiro, Shengwei An, Pin-Yu Chen, Xiangyu Zhang, Ninghui Li
    Proceedings of the 32nd Network and Distributed System Security Symposium (NDSS 2025)
    [paper] [code] [slides] [twitter] [website]
  • ProSec: Fortifying Code LLMs with Proactive Security Alignment
    Xiangzhe Xu*, Zian Su*, Jinyao Guo, Kaiyuan Zhang, Zhenting Wang, Xiangyu Zhang
    Preprint 2024
    [paper] [code]
  • ProRec: Source Code Foundation Models are Transferable Binary Analysis Knowledge Bases
    Zian Su, Xiangzhe Xu, Ziyang Huang, Kaiyuan Zhang, Xiangyu Zhang
    Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)
    [paper] [code]
  • Exploring the Orthogonality and Linearity of Backdoor Attacks
    Kaiyuan Zhang*, Siyuan Cheng*, Guangyu Shen, Guanhong Tao, Shengwei An, Anuran Makur, Shiqing Ma, Xiangyu Zhang
    Proceedings of the 45th IEEE Symposium on Security and Privacy (S&P 2024)
    [paper] [code] [slides] [video] [poster] [twitter] [website]
  • FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning
    Kaiyuan Zhang, Guanhong Tao, Qiuling Xu, Siyuan Cheng, Shengwei An, Yingqi Liu, Shiwei Feng, Guangyu Shen, Pin-Yu Chen, Shiqing Ma, Xiangyu Zhang
    Proceedings of the Eleventh International Conference on Learning Representations (ICLR 2023)
    Also appears in ECCV 2022 Workshop on Adversarial Robustness in the Real World (AROW 2022), Best Paper Award 🏆
    [paper] [code] [slides] [media coverage]

Selected Honors & Awards

  • Apple Scholar Nominee, 2025
  • Amazon Fellowship, 2024
  • InnovatED Award, Purdue University, 2023
  • Best Paper Award, ECCV AROW Workshop, 2022
  • Summer Research Grant, Purdue University, 2022
  • National Scholarship, 2016
  • Multiple Travel Grants: NDSS 2025, IEEE S&P 2024, ACM CCS 2020, etc.

Teaching

Guest Lecture

Teaching Assistant

Professional Services

  • Organizers
    • The 1st Workshop on Backdoor Attacks and Defenses in Machine Learning (BANDS) at ICLR, 2023
    • Machine Learning & Security Seminar at Purdue University, 2021, 2022, 2023
  • Program Committee Member
    • International Conference on Learning Representations (ICLR), 2024, 2025
    • International Conference on Machine Learning (ICML), 2023, 2024, 2025
    • Advances in Neural Information Processing Systems (NeurIPS), 2023, 2024, 2025
    • IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
    • IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023
    • ICLR Workshop on Privacy Regulation and Protection in Machine Learning, 2024
    • ICML Workshop on Federated Learning and Analytics in Practice, 2023
    • ICML Workshop on Adversarial Machine Learning Frontiers, 2022
  • Journal Reviewers
    • IEEE Transactions on Information Forensics and Security (TIFS), 2023, 2024, 2025
    • IEEE Transactions on Dependable and Secure Computing (TDSC), 2023
    • ACM Transactions on Privacy and Security (TOPS), 2023
  • External Reviewers
    • ACM Conference on Computer and Communications Security (CCS), 2021, 2022, 2023, 2024, 2025
    • USENIX Security Symposium (USENIX Security), 2024, 2025
    • IEEE Conference on Secure and Trustworthy Machine Learning (SaTML), 2025
    • ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA), 2024
    • IEEE/ACM International Conference on Automated Software Engineering (ASE), 2023
  • Student Volunteers
    • ICML 2021, ICLR 2021, ECOOP/ISSTA 2021, CCS 2020, SIGMOD 2020, etc.

Personal

  • Kaiyuan Zhang’s name is pronounced as
  • I love basketball and have been playing weekly for over ten years.
  • I’m a big fan of tennis, especially the moments of hitting the ball with the right amount of spin and force.
  • I enjoy kayaking, quietly exploring a creek, enjoy views that can’t be seen from shore.
  • I also like reading, drinking, cooking, traveling, and, of course, boba :-)
  • I consider myself lucky to be guided by helpful advice and instructions. Here are some notes I collect from time to time.