Zico Kolter

Zico Kolter is a Professor and Director of the Machine Learning Department with the School of Computer Science at Carnegie Mellon University. His group’s work focuses on machine learning very broadly. Much of their work aims at making deep learning algorithms more robust, safer, and understanding how data impacts how models function. To these ends, they have worked on methods for assessing and improving the robustness of deep learning systems, building complex “modules” (such as optimization solvers) within the loop of deep architectures, and building new types of architectures for deep networks.

Zico completed his Ph.D. in computer science at Stanford University in 2010, followed by a postdoctoral fellowship at MIT from 2010 to 2012. Throughout his career, he has made significant contributions to the field of machine learning, authoring numerous award-winning papers at prestigious conferences such as NeurIPS, ICML, and AISTATS.