Wenxin Ding
PhD Student at University of Chicago
About Me
I am a third-year PhD student in the Computer Science department at University of Chicago. I am advised by Prof. Heather Zheng and Prof. Ben Zhao. My research focuses on security and privacy in machine learning. I received my bachelor’s degrees in Computer Science and Mathematical Sciences with a minor in Computational Finance from Carnegie Mellon University in 2020. I received my master’s degree in Computer Science – Research Thesis from Carnegie Mellon University in 2021, jointly advised by Prof. Nihar Shah and Prof. Weina Wang.
Email: wenxind [at] uchicago.edu
Education
University of Chicago
- PhD student in Computer Science 2021–
Carnegie Mellon University
-
M.S. in Computer Science – Research Thesis 2020–2021
-
B.S. (Hons) in Computer Science 2016–2020
-
B.S. (Hons) in Mathematical Sciences 2016–2020
Publication
- Towards Scalable and Robust Model Versioning
(Wenxin Ding, Arjun Nitin Bhagoji, Ben Y. Zhao, Haitao Zheng)
- 2nd IEEE Conference on Secure and Trustworthy Machine Learning
- Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models
(Shawn Shan, Wenxin Ding, Josephine Passananti, Haitao Zheng, Ben Y. Zhao)
- 45th IEEE Symposium on Security and Privacy (S&P 2024)
- MIT Technology Review
- Characterizing the Optimal 0-1 Loss for Multi-class Classification with a Test-time Attacker
(Sihui Dai*, Wenxin Ding*, Arjun Nitin Bhagoji, Daniel Cullina, Ben Y. Zhao, Haitao Zheng, Prateek Mittal)
- Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023) (Spotlight)
- Post-breach Recovery: Protection against White-box Adversarial Examples for Leaked DNN Models
(Shawn Shan, Wenxin Ding, Emily Wenger, Haitao Zheng, Ben Y. Zhao)
- 2022 ACM Conference on Computer and Communications Security (CCS)
- Calibration with Privacy in Peer Review
(Wenxin Ding, Gautam Kamath, Weina Wang, Nihar B Shah)
- 2022 IEEE International Symposium on Information Theory (ISIT)
- 2022 AAAI Privacy-Preserving Artificial Intelligence (PPAI-22) workshop spotlight (click for video presentation)
- On the Privacy-Utility Tradeoff in Peer-Review Data Analysis (Wenxin Ding, Nihar B. Shah, Weina Wang)
Teaching Assistant
University of Chicago
- CMSC 25300/35300 Mathematical Foundations of Machine Learning
Carnegie Mellon University
- 15110 Principles of Computing (Head TA)
- 15213 Introduction to Computer Systems
- 15440 Distributed Systems
Awards
- 2021 University of Chicago Eckhardt Scholar
- 2020 Carnegie Mellon University Senior Leadership Recognition
- 2019 Mark Stehlik SCS Alumni Undergraduate Impact Scholarship
- 2017 William Lowell Putnam Mathematical Competition (Rank: 255 / 4638)