William Cai

I am a PhD student in the Department of Management Science and Engineering at Stanford, working in the Stanford Computational Policy Lab. I research real-world decision making systems, with a focus on (1) designing algorithmic policies which are robust to and can efficiently ameliorate inequities, and (2) developing statistical methodology for assessing equity in complex systems. My work is supported by a Stanford Graduate Fellowship. I spent the summer of 2020 as a research intern on Facebook's Responsible AI team and worked as a RA at Microsoft Research New York in the computational social science group from 2017-2018 before starting my PhD.

Research (Google Scholar)

Adaptive Sampling Strategies to Construct Equitable Training Datasets

William Cai, Ro Encarnacion, Bobbie Chern, Sam Corbett-Davies, Miranda Bogen, Stevie Bergman, Sharad Goel. ACM FAccT 2022.

A Causal Framework for Observational Studies of Discrimination

Johann Gaebler, William Cai, Guillaume Basse, Ravi Shroff, Sharad Goel, Jennifer Hill. Statistics and Public Policy (Forthcoming).

Bandit Algorithms to Personalize Educational Chatbots

William Cai , Joshua Grossman, Zhiyuan Lin, Hao Sheng, Johnny Tian-Zheng Wei, Joseph Jay Williams, Sharad Goel. Machine Learning.

Fair Allocation through Selective Information Acquisition

William Cai , Johann Gaebler, Nikhil Garg, Sharad Goel. AIES 2020.

Objecting to experiments that compare two unobjectionable policies or treatments

Michelle N. Meyer, Patrick R. Heck, Geoffrey S. Holtzman, Stephen M. Anderson, William Cai , Duncan J. Watts, Christopher F. Chabris. PNAS 2019.