Kaiyuan Zhang Kaiyuan Zhang | 张开元

Ph.D. Student
Department of Computer Science
Purdue University
305 N. University Street
West Lafayette, IN 47907
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, especially in safe & responsible language models, generative models and distributed training.

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. I was a research intern at NEC Labs America.

Research Opportunities: I am always happy to discuss and brainstorm; if you’re a researcher/student (especially underrepresented minorities) interested in security, privacy, or robust AI (Generative AI most recent, e.g., GPT, Llama, PaLM, DALL-E), please reach out with subject “[Prospective collaboration]” to zhan4057 at purdue dot edu.

What’s New

  • 03/2024. I will join Amazon Bedrock (Generative AI, Seattle) as an Applied Scientist Intern this summer!
  • 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!

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

  • Exploring the Orthogonality and Linearity of Backdoor Attacks
    Kaiyuan Zhang*, Siyuan Cheng*, Guangyu Shen, Guanhong Tao, Shengwei An, Anuran Makur, Shiqing Ma, Xiangyu Zhang
    To Appear at Proceedings of the 45th IEEE Symposium on Security and Privacy (Oakland 2024)
    [paper (coming soon)] [code (coming soon)]
  • 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
    [paper] [code] [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 Machine Learning (ICML), 2023, 2024
    • Neural Information Processing Systems (NeurIPS), 2023
    • International Conference on Learning Representations (ICLR), 2024
    • 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
  • External Reviewers
    • ACM Conference on Computer and Communications Security (CCS)
    • USENIX Security Symposium (Security)
    • IEEE/ACM International Conference on Automated Software Engineering (ASE)
    • ACM SIGSOFT International Symposium on Software Testing and Analysis (ISSTA)
    • International Conference on Computer-Aided Verification (CAV)
  • Student Volunteers
    • ICML 2021, ICLR 2021, ECOOP/ISSTA 2021, CCS 2020, SIGMOD 2020