Michael P. Kim



I am a Ph.D. student with the Stanford Theory Group. Broadly, I am interested in algorithms, complexity theory, and their applications to the sciences. Recently, my work has focused on fairness in data analysis.

I am fortunate to be advised by Omer Reingold. During my master's, I had the pleasure of working with Virginia Vassilevska Williams.

publication highlights (all)

Multiaccuracy: Black-Box Post-Processing for Fairness in Classification [arXiv]
MPK, Amirata Ghorbani, James Zou
AAAI AI, Ethics, and Society 2019

Fairness Through Computationally-Bounded Awareness [arXiv]
MPK, Omer Reingold, Guy N. Rothblum
NeurIPS 2018

Calibration for the (Computationally-Identifiable) Masses [arXiv]
Úrsula Hébert-Johnson, MPK, Omer Reingold, Guy N. Rothblum
ICML 2018

teaching and writings

Teaching has been a big part of my career as a Stanford student.
Here are notes from some of the lectures I've given.