Backed by $12.5M in federal funding, Univ. of Washington leads new data science institute

Maryam Fazel, a University of Washington electrical and computer engineering professor, will lead the multidisciplinary Institute for Foundations of Data Science (IFDS). Fazel is pictured with colleagues in this 2015 photo. (UW Photo / Patrick Bennett) With $12.5 million in federal funding, the University of Washington will lead a cohort […]

Maryam Fazel, a University of Washington electrical and computer engineering professor, will lead the multidisciplinary Institute for Foundations of Data Science (IFDS). Fazel is pictured with colleagues in this 2015 photo. (UW Photo / Patrick Bennett)

With $12.5 million in federal funding, the University of Washington will lead a cohort of institutions tackling foundational challenges in the field of data science.

The UW is teaming up with interdisciplinary researchers from University Wisconsin-Madison, University California-Santa Cruz and University of Chicago to form the Institute for Foundations of Data Science (IFDS). The effort will be led by Maryam Fazel, a UW electrical and computer engineering professor.

The institute marks the culmination of three years of work supported by the National Science Foundation as part of its Transdisciplinary Research in Principles of Data Science, or TRIPODS, program. The effort is part of the NSF’s Harnessing the Data Revolution Big Idea project.

“As data science is increasingly incorporated in all facets of our lives, its success is uncovering pressing challenges that call for new theories,” Fazel said in a statement. “We need the expertise of all core disciplines to understand the mysteries and to address the pitfalls of data science and artificial intelligence algorithms.”

The UW team for the IFDS, clockwise from top left: Maryam Fazel, Zaid Harchaoui, Kevin Jamieson, Yin Tat Lee, Abel Rodriguez and Dmitriy Drusvyatskiy. (UW Image)

As explained by the NSF, the institute “will lead to methods that are more computationally efficient, robust to errors and incomplete or ambiguous data, and better able to respond and act in changing environments. The team will also study the ethical and societal implications of data-driven algorithms, including privacy, unfairness and bias.” The funding is spread over five years.

NSF has funded a second data science institute and consortium of universities that is being led by the University of California-Berkeley and Massachusetts Institute of Technology.

The UW team includes Zaid Harchaoui, an associate professor of statistics; Dmitriy Drusvyatskiy, an associate professor of mathematics; Kevin Jamieson and Yin Tat Lee, assistant professors in the Paul G. Allen School of Computer Science & Engineering; and Abel Rodriguez, professor and chair of the statistics department.

The institute will collaborate with the UW’s eScience Institute and the NSF AI Institute that includes the UW.

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