FODA Institute Foundations of Data Analysis

Foundations of Data Analysis

The UC Berkeley FODA Institute is an NSF TRIPODS institute designed to make transformational advances in the interdisciplinary foundations of data science, including both research and teaching.

Research Focus

• Algorithms, inference, and fundamental tradeoffs
• Stability as a computational-inferential principle
• Data-driven computational mathematics
• Combining science-based models with data-driven models

Application areas, including via the TRIPODS+X program, include genetics, neuroscience, materials science, astronomy/cosmology, and social sciences.

We are co-funding several fellowships with the Berkeley Institute of Data Science (BIDS) and the Simons Institute for the Theory of Computing to pursue these research directions and applications.

In coordination with the new Division of Data Sciences, we are involved with curricular development and reorganization, bringing computational and inferential approaches to undergraduates.

Organization

FODA Institute PIs/coPIs: Michael Mahoney (Director), Bin Yu, Fernando Perez, Michael Jordan, Dick Karp, Peter Bartlett (not shown), and Uros Seljak (not shown, as a coPI with TRIPODS+X).

We are pleased to welcome the following post-doctoral fellows:

• Michal Derezinski
• Jelena Diakonikolas
• Amir Gholaminejad
• Wooseok Ha
• Rajiv Khanna
• Francois Lanusse
• Yian Ma
• Yan Shuo Tan

Campus Partners

Other campus organizations working on related aspects of data science include:

• Berkeley Institute for Data Science (BIDS)
• Simons Institute for the Theory of Computing
• RISE (Real-time Intelligent Secure Explainable) Lab
• Lawrence Berkeley National Laboratory (LBNL)

News

• Berkeley defining the next academic frontier: Two NSF awards to UC Berkeley set the stage for a new era of Data Science (press release October 17, 2017)

Acknowledgement

The FODA Institute is supported by a grant from the National Science Foundation.