Researchers

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, large-scale learning, tractable pricing of prediction markets, and learning with gauge regularization.

He received his PhD from Princeton in 2007. He is a co-creator of the MaxEnt package for modeling species distributions, which is used by biologists around the world to design national parks, model impacts of climate change, and discover new species.