Yue Gao 高越

Ph.D. Student • University of Wisconsin at Madison

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I am a Ph.D. student in the Computer Science Department at the University of Wisconsin–Madison, advised by Kassem Fawaz in the Wi-Pi and MadS&P research group. I also work with Nicolas Papernot on adversarial machine learning. Prior to joining UW–Madison, I obtained my Bachelor’s degree in Computer Science from Shanghai University.

My research interest broadly lies in machine learning security and system security. My current works focus on the adversarial robustness of machine learning systems, with the goal of understanding, detecting, and mitigating vulnerabilities in real-world machine learning systems.

  News


Oct 11, 2022 Gave a talk about the limitations of stochastic pre-processing defenses (slides).
Oct 8, 2022 Recognized as a Top Reviewer (10%) for NeurIPS 2022.
Oct 3, 2022 Wrote a blogpost about stochastic pre-processing defenses.
Sep 14, 2022 Our paper On the Limitations of Stochastic Pre-processing Defenses was accepted by NeurIPS 2022.
Sep 9, 2022 Our paper about defending against textual backdoor attacks was accepted by MILCOM 2022.
May 14, 2022 Our paper The Interplay Between Vulnerabilities in Machine Learning Systems was accepted by ICML 2022 as long presentation (top 2% of all papers).
May 2, 2022 Our paper Experimental Security Analysis of the App Model in Business Collaboration Platforms was accepted by USENIX Security 2022.

  Selected Publications


  1. NeurIPS
    On the Limitations of Stochastic Pre-processing Defenses
    In Proceedings of the 36th Conference on Neural Information Processing Systems 2022
  2. USENIX Security
    Experimental Security Analysis of the App Model in Business Collaboration Platforms
    Yunang Chen*, Yue Gao*, Nick Ceccio, Rahul ChatterjeeKassem Fawaz, and Earlence Fernandes
    In 31st USENIX Security Symposium (USENIX Security 22) Aug 2022
  3. ICML
    Rethinking Image-Scaling Attacks: The Interplay Between Vulnerabilities in Machine Learning Systems
    Yue GaoIlia Shumailov, and Kassem Fawaz
    In Proceedings of the 39th International Conference on Machine Learning Jul 2022
    Accepted for Long Presentation (2%)
  4. MILCOM
    I Know Your Triggers: Defending Against Textual Backdoor Attacks With Benign Backdoor Augmentation
    Yue GaoJack W. Stokes, Manoj Prasad, Andrew Marshall, Kassem Fawaz, and Emre Kiciman
    In 2022 IEEE Military Communications Conference, MILCOM 2022 Nov 2022
  5. CVPR Workshop
    Variational Autoencoder for Low Bit-rate Image Compression
    Lei Zhou*, Chunlei Cai*, Yue Gao, Sanbao Su, and Junmin Wu
    In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops Nov 2018
    Winner of the 1st Workshop and Challenge on Learned Image Compression.