John Miller

John Miller 

John Miller
Machine learning researcher
Quantitative trader
Github / Google Scholar

About Me

I obtained my PhD in Electrical Engineering and Computer Sciences from UC Berkeley in August 2022. I was advised by Moritz Hardt and Ben Recht. Throughout my PhD, I was generously supported by the Berkeley Fellowship and the NSF Graduate Research Fellowship. From 2016-2017, I was a research scientist in Baidu's Silicon Valley AI Lab. Before that, I received a BS in Computer Science and an MS in Electrical Engineering from Stanford University, where I had the privilege of working with Percy Liang and Tim Roughgarden.


(asterisk indicates joint or alphabetical authorship)


  • Before graduate school, I wrote CVXCanon, a package for canonicalization of convex programs that's used in CVXPY and CVXR.

  • I maintain Folktables, a Python package that provides access to datasets derived from US Census data.

  • I was also the main contributor to WhyNot, a Python package that provides an experimental sandbox for causal inference and decision making in dynamic environments.