Kameron Shahabi

About

I am a first-year Ph.D. student in computer science at the University of Washington, fortunate to be advised by Prof. Rachel Lin. I did my undergrad at USC, where I had the pleasure of working with Prof. Vatsal Sharan on robustness and fairness in machine learning.

My interests lie at the intersection of machine learning, cryptography, and complexity theory. This includes algorithmic fairness, verifiable ML, privacy, and the hardness of learning.

Publications

• Mitigating Simplicity Bias in Deep Learning for Improved OOD Generalization and Robustness
  Bhavya Vasudeva, Kameron Shahabi, Vatsal Sharan
  Transactions on Machine Learning Research, 2024
  arXiv | pdf

• Towards Accurate Spatiotemporal COVID-19 Risk Scores Using High-Resolution Real-World Mobility Data
  Sirisha Rambhatla, Sepanta Zeighami, Kameron Shahabi, Cyrus Shahabi, Yan Liu
  ACM Transactions on Spatial Algorithms and Systems, 2022
  arXiv | pdf

Projects

• Estimated Cost of Scaling Contact Discovery Using Private Set Intersection
  Kameron Shahabi, Rolfe Schmidt
  Whitepaper with Signal, 2023
  code | pdf
  

Education

• Ph.D. in Computer Science, University of Washington
  September 2024 - Present

• M.S. in Computer Science, University of Southern California
  August 2023 - May 2024

• B.S. in Computer Science, University of Southern California
  August 2019 - May 2023