Stefanie Jegelka is a postdoc at UC Berkeley, working with Michael Jordan and Trevor Darrell. She is a member of the AMPlab and a visitor at the International Computer Science Institute. In 2015, she will join the EECS Department at MIT as an assistant professor.
Before joining Berkeley, Dr. Jegelka completed her PhD in Bernhard Schölkopf's group at the Max Planck Institutes in Tübingen and graduated from ETH Zurich. During her PhD, she worked with Jeff Bilmes, and before that with Ulrike von Luxburg and Arthur Gretton.
Her research focuses on combinatorial problems in Machine Learning, in particular how to exploit nice mathematical structure for new models and efficient algorithms. Her research interests include submodularity and discrete optimization, graph problems, graphical models, kernel methods and clustering, distributed machine learning, and applications e.g. in computer vision and biology.