Vikram Kher

Vikram Kher

2nd Year PhD Student

Yale University

I am a 2nd year PhD student in the Yale Theory Group advised by Manolis Zampetakis. My research focuses on the intersection of algorithmic game theory and learning theory. As a researcher, I am deeply motivated to address the challenges of designing transparent, fair, and assumption-lean algorithmic systems. In particular, my overarching research goals are to:

  • Develop theoretical models of economic and social exchanges that are realistic, easily interpretable, and require minimal assumptions,
  • Design algorithms with robust guarantees for equitable outcomes,
  • Prioritize algorithms that offer efficiently checkable certificates to validate their results.

During my undergrad at USC, I was fortunate to work with Prof. David Kempe on algorithms for fair committee elections and with Prof. Assad Oberai on using machine learning to predict COVID-19 disease severity. In 2022, I participated in the DIMACS REU, where I worked with Dr. Ariel Schvartzman on topics in auction theory.

Interests
  • Algorithmic Game Theory
  • Auction Theory
  • Learning from Samples
  • Computational Social Choice
Education
  • PhD in Computer Science, 2028 (Expected)

    Yale University

  • BS in Computer Science, Summa Cum Laude, 2022

    University of Southern California

  • BA in Applied and Computational Mathematics, Summa Cum Laude, 2022

    University of Southern California

Publications

(2023). Proportional Representation in Metric Spaces and Low-Distortion Committee Selection. The 38th Annual AAAI Conference on Artificial Intelligence.

PDF Cite

(2023). Fine-Grained Buy-Many Mechanisms Are Not Much Better Than Bundling. Proceedings of the 24th ACM Conference on Economics and Computation.

PDF Cite

(2021). Machine learning based predictors for COVID-19 disease severity. Journal of Scientific Reports.

PDF Cite

Contact