William Overman
William Overman

PhD Student

Stanford University
Graduate School of Business

About Me

Hi, I’m a PhD student at Stanford Graduate School of Business in the Operations, Information, and Technology group. My research interests span machine learning, experimentation, and healthcare, with a focus on alignment, uncertainy quantification, reinforcement learning (RL), network interference in experiments, and prediction models in healthcare operations and clinical settings. I have interned at Uber, where I applied my research in RL and experimentation to large-scale problems.

I completed my undergraduate studies at Caltech, double majoring in mathematics and computer science, with a focus on combinatorics and complexity theory. After graduating in Spring 2020, I spent most of the COVID-19 pandemic in South Korea as a visiting researcher at the Institute for Basic Science. During this time, I also obtained a master’s degree in computer science from UC Irvine, focusing on research in multi-agent reinforcement learning.

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Interests
  • Reinforcement Learning
  • Alignment
  • Experimentation
  • Uncertainty Quantification
  • Healthcare
Education
  • PhD Operations, Information, and Technology

    Stanford University

  • MS Computer Science

    University of California, Irvine

  • BSc Mathematics and Computer Science (double major)

    California Institute of Technology

Featured Publications
Recent Publications
(2024). Aligning Model Properties via Conformal Risk Control.
(2024). Beating Price of Anarchy and Gradient Descent without Regret in Potential Games. The Twelfth International Conference on Learning Representations.
(2022). Global Convergence of Multi-Agent Policy Gradient in Markov Potential Games. International Conference on Learning Representations.