Stefanie Jegelka is the X-Consortium Career Development Assistant Professor at MIT EECS, and a member of CSAIL,IDSS and Machine Learning at MIT. Before that, she was a postdoc in the AMPlab and computer vision group at UC Berkeley, and before that a PhD student at the Max Planck Institutes in Tuebingen and at ETH Zurich.

 

Her research revolves around designing models and efficient algorithms for machine learning problems, in particular with discrete and combinatorial structure. This involves machine learning, optimization, discrete mathematics, algorithms,... More specifically, she has worked on submodular functions in machine learning, graph problems, graphical models, kernel methods and clustering, distributed machine learning, and applications e.g. in computer vision and biology.