About

The Research Pod in Machine Learning brings together researchers from theoretical computer science, mathematics, statistics, electrical engineering, and economics to develop the theoretical foundations of machine learning and data science. Led by Peter Bartlett, this pod is partially funded by a $12.5 million award made under the National Science Foundation's program on Transdisciplinary Research in Principles of Data Science to establish the Foundations of Data Science Institute (FODSI). This institute, a collaboration between UC Berkeley and MIT, partnering with Boston, Northeastern, Harvard and Howard universities, as well as Bryn Mawr College, aims to improve our understanding of critical issues in data science, including modeling, statistical inference, computational efficiency, and societal impacts. NSF, together with the Simons Foundation, is also supporting the activities of the pod through the Collaboration on the Theoretical Foundations of Deep Learning. This is a collaboration of 11 PIs from eight institutions around the world that aims to understand the mathematical mechanisms that underpin the practical success of deep learning. The Simons Institute will act as the convening center for many of these activities, hosting public events such as summer schools, research workshops, and other collaborative research opportunities.

To participate as a fellow in the Simons ML Pod, apply directly to one of the following two programs:

 

Also, the Simons Institute programs in AY 24-25 may be of special interest to machine learning researchers. Information on  applying for a fellow position in one of the semester-long programs is here.

 

Supported by:

     

Pod Directors

Peter Bartlett (UC Berkeley)

Machine Learning Postdoctoral Researchers

Keaton Ellis (University of Maryland)
Gautam Goel (UC Berkeley)
Soufiane Hayou (National University of Singapore)
Jingfeng Wu (UC Berkeley)
Lydia Zakynthinou (UC Berkeley)

Past Participants

Stephen Bates (UC Berkeley)
Machine Learning Postdoctoral Researcher
Luiz Fernando de Oliveira Chamon (University of Pennsylvania)
Machine Learning Postdoctoral Researcher
Lin Chen (UC Berkeley)
Machine Learning Postdoctoral Researcher
Sitan Chen (Massachusetts Institute of Technology)
Machine Learning Postdoctoral Researcher
Yuval Dagan (UC Berkeley)
Machine Learning Postdoctoral Researcher
Mahsa Derakhshan (University of Maryland)
Machine Learning Postdoctoral Researcher
Spencer Frei (UC Los Angeles)
Machine Learning Postdoctoral Researcher
Spencer Frei (UC Berkeley)
Machine Learning Postdoctoral Researcher
Paul Goelz (UC Berkeley)
Machine Learning Postdoctoral Researcher
Yanjun Han (UC Berkeley)
Machine Learning Postdoctoral Researcher
Christopher Harshaw (UC Berkeley)
Machine Learning Postdoctoral Researcher
Wei Hu (UC Berkeley)
Machine Learning Postdoctoral Researcher
Frederic Koehler (Massachusetts Institute of Technology)
Machine Learning Postdoctoral Researcher
Omar Montasser (Toyota Technological Institute at Chicago)
Machine Learning Postdoctoral Researcher
Chara Podimata (Harvard University)
Machine Learning Postdoctoral Researcher
Mingda Qiao (Stanford University )
Machine Learning Postdoctoral Researcher
Adil Salim (KAUST)
Machine Learning Postdoctoral Researcher
Dennis Shen (Massachusetts Institute of Technology)
Machine Learning Postdoctoral Researcher
Jan van den Brand (KTH Royal Institute of Technology)
Machine Learning Postdoctoral Researcher
Ellen Vitercik (UC Berkeley)
Machine Learning Postdoctoral Researcher
Machine Learning Postdoctoral Researcher
Carrie Wu (Stanford University)
Machine Learning Postdoctoral Researcher
Manolis Zampetakis (UC Berkeley)
Machine Learning Postdoctoral Researcher
Andrea Zanette (Stanford University)
Machine Learning Postdoctoral Researcher
Angela Zhou (UC Berkeley)
Machine Learning Postdoctoral Researcher