Kaiyuan Zhang Kaiyuan Zhang | 张开元

Ph.D. Student
Department of Computer Science
Purdue University
Email: zhan4057 at purdue dot edu
Google Scholar | dblp | Twitter | GitHub | LinkedIn

I am a Ph.D. student in the Department of Computer Science at Purdue University, advised by Prof. Ninghui Li and Prof. Xiangyu Zhang. My research interests focus on security and privacy in machine learning.

Before joining Purdue, I spent a wonderful year as a visiting graduate student at the University of Illinois at Urbana-Champaign, 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 (especially women and underrepresented minorities) interested in security, privacy, or robust AI (foundation models most recent, e.g., GPT-4, PaLM, DALL-E), please reach out to me!

What’s New

  • 09/2023. Excited to be featured in NEC News for the summer intern project!
  • 05/2023. I will join NEC Labs America (San Jose) as a Research Intern this summer!
  • 11/2022. I am co-organizing the workshop on Backdoor Attacks and Defenses in Machine Learning (BANDS) at ICLR 2023! We invite submissions on any aspect of backdoor attacks and defenses in machine learning!
  • 10/2022. Excited to be featured in Purdue News for the Best Paper Award at ECCV 2022 AROW Workshop!
  • 10/2022. Happy to receive Best Paper Award from ECCV 2022 Workshop on Adversarial Robustness in the Real World!

Selected Publications [Full List] [Google Scholar]

  • 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)
    ECCV 2022 Workshop on Adversarial Robustness in the Real World (AROW 2022), Best Paper Award 🏆
    Press: Purdue News
    [bib] [code] [paper] [workshop slides]

Selected Awards

  • Best Paper Award at ECCV 2022 AROW Workshop, October 2022
  • Purdue University Summer Research Grant Award, April 2022
  • ACM CCS Student Conference Grant, October 2020
  • China National Scholarship (0.2% in China), November 2016

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
  • Journal Reviewers
    • IEEE Transactions on Information Forensics and Security (TIFS)
    • IEEE Transactions on Dependable and Secure Computing (TDSC)
    • ACM Transactions on Privacy and Security (TOPS)
  • Conference/Workshop Reviewers
    • International Conference on Learning Representations (ICLR), 2024
    • Neural Information Processing Systems (NeurIPS), 2023
    • International Conference on Machine Learning (ICML), 2023
    • Conference on Computer Vision and Pattern Recognition (CVPR), 2024
    • IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023
    • ICML Workshop on Federated Learning and Analytics in Practice, 2023
    • ICML Workshop on Adversarial Machine Learning Frontiers, 2022
  • External Reviewers
    • USENIX Security Symposium
    • ACM Conference on Computer and Communications Security (CCS)
    • IEEE/ACM International Conference on Automated Software Engineering (ASE)
    • International Conference on Computer-Aided Verification (CAV)
  • Student Volunteers
    • ICML 2021, ICLR 2021, ECOOP/ISSTA 2021, CCS 2020, SIGMOD 2020