I am a Postdoctoral Scholar in the Department of Computer Science at the University of Chicago working with Ben Zhao and Nick Feamster. My research focuses on the security of machine learning algorithms. I have also recently begun working on the use of machine learning algorithms for security applications, specifically in networking. I completed my Ph.D. under the supervision of Prateek Mittal in the Department of Electrical and Computer Engineering at Princeton University. For an accessible overview of my research, see Research and for a full list of papers, see Publications.

News

  • 01/2022: AISTATS 2022 paper on defending against model poisoning attack is up. Congratulations Ashwinee!
  • 12/2021: New pre-print on poisoning attack forensics is up!
  • 11/2021: Selected for the UChicago Rising Stars in Data Science.
  • 09/2021: Paper on defenses against website fingerprinting attacks is accepted to AISec 2021. Congratulations Shawn!
  • 07/2021: Paper on lower bounds on cross-entropy loss for classification with test-time attacks is appearing at IMCL 2021! Follow-up to our NeurIPS 2019 paper which introduced this line of work on fundamental lower bounds on loss in the presence of test-time attackers.
  • 06/2021: Our paper on physical backdoor attacks is appearing at CVPR 2021.
  • 05/2021: Runner-up for the Bede Liu Best Dissertation award from the Department of Electrical and Computer Engineering at Princeton University for my thesis The Role of Data Geometry in Adversarial Machine Learning.
  • 10/2020: Excited to join the Department of Computer Science and CDAC at the University of Chicago as a postdoc.
  • 09/2020: Successfully defended my thesis!