Stefanie Jegelka


I am an X-Consortium Career Development Associate Professor at MIT EECS, and a member of CSAIL, IDSS, the Center for Statistics and Machine Learning at MIT. I am also affiliated with the ORC.
Before that, I was a postdoc in the AMPlab and computer vision group at UC Berkeley, and a PhD student at the Max Planck Institutes in Tuebingen and at ETH Zurich.

My research is in algorithmic machine learning, and spans modeling, optimization algorithms, theory and applications. In particular, we have been working on exploiting mathematical structure for discrete and combinatorial machine learning problems, for robustness and for scaling machine learning algorithms.
More details about my research can be found in these publications.

Our research is supported by an NSF CAREER Award, a DARPA Young Faculty Award, an NSF BIGDATA, an Adobe Research award, an STL award and other awards by NSF and DARPA. Previously, we were also supported by a Google Research Award and an MIT RSC award. Thanks!

If you would like to work with me:
Please apply to the EECS graduate program. I am happy to talk when you are here.
Unfortunately, I am not able to take on any interns.


Oral at ICLR, congrats Keyulu and Weihua!

Best Paper at NeurIPS Relational Representation Learning workshop. Congrats Charlotte and David!

NeurIPS 2018 tutorial on Negative Dependence

4 papers accepted at NeurIPS (2 Spotlights).

Papers accepted at ICML and UAI. Congratulations Keyulu, Chengtao and Alkis!

I was selected as a 2018 Sloan Research Fellow

Chengtao Li wins Baidu fellowship. Congratulations!