Portrait of Miro Dudík

Miro Dudík

Senior Principal Researcher


Miro Dudík’s research focuses on combining theoretical and applied aspects of machine learning, statistics, convex optimization and algorithms. Most recently he has worked on contextual bandits, reinforcement learning, and algorithmic fairness.

He received his PhD from Princeton in 2007. He is a co-creator of the Fairlearn toolkit for assessing and improving the fairness of machine learning models and of the Maxent package for modeling species distributions, which is used by biologists around the world to design national parks, model the impacts of climate change, and discover new species.