Stefanie Jegelka
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I am an Associate Professor (on leave) at MIT EECS, and a Humboldt Professor at TU Munich. At MIT, I am 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 has been supported by a Sloan Research Fellowship, an NSF CAREER Award, a DARPA Young Faculty Award, an NSF BIGDATA award, an ONR MURI, faculty research awards by Google, Two Sigma and Adobe, an STL award and other awards by NSF and DARPA. Thanks!
NEWS
3 workshop best paper awards at ICML 2024 (High-dimensional learning dynamics and ICL)! Congratulations Behrooz, Derek and Theo, and Yifei!
Nisha is joining Georgia Tech as an Assistant Professor. Congratulations!
Keyulu received MIT's
Derek received an NSF Fellowship. Ching-Yao received an IBM fellowship. Congratulations!
Our NSF AI Institute for Optimization was funded
I will give a sectional lecture at the International Congress of Mathematicians (ICM) 2022
I will give a semi-plenary at ISMP 2022
I am serving as a program chair for ICML 2022