2216970

Institute for Data, Econometrics, Algorithms and Learning (IDEAL)

The Institute for Data, Econometrics, Algorithms, and Learning (IDEAL) will consolidate and amplify research devoted to the foundations of data science across all the major research-focused educational institutions in the greater Chicago area: the University of Illinois at Chicago, Northwestern University, the Toyota Technological Institute at Chicago, the University of Chicago, and the Illinois Institute of Technology.

This transdisciplinary institute involves over 50 researchers working on key aspects of the foundations of data science across computer science, electrical engineering, mathematics, statistics, and several related fields like economics, operations research, and law, and they are complemented by members of Google's Learning Theory team. Its research goals range from the core foundations of data science to its interfaces with other disciplines:

1) Tackling important challenges related to foundations of machine learning and optimization,
2) Addressing statistical, algorithmic and mathematical challenges in dealing with high-dimensional data, and
3) Exploring the foundations of aspects of data science that interact with society.

The institute will foster strong connections with the community and local high schools, broaden participation in data science locally and nationally, and build lasting research and educational infrastructure through its activities. Institute activities will include workshops for undergraduate students, high school teacher workshops, public lectures, and museum exhibit designs. These will build new pathways for undergraduate students, high school students, and the broader public from diverse and underrepresented backgrounds, to increase participation and engagement with scientific fields related to data science.

The research thrusts of the institute will center around the foundations of machine learning, high-dimensional data analysis and inference, and data science and society. Specific topics include foundations of deep learning, reinforcement learning, machine learning and logic, network inference, high-dimensional data analysis, trustworthiness & reliability, fairness, and data science with strategic agents. The research activities are designed to facilitate collaboration between the different disciplines and across the five Chicago-area institutions, and they build on the extensive experience from previous efforts of the participating universities. The activities include topical special programs, postdoctoral fellows, co-mentored PhD students, workshops, coordinated graduate courses, visiting fellows, research meetings, and brainstorming sessions.

The proposed research will lead to new theoretical frameworks, models, mathematical tools and algorithms for analyzing high-dimensional data, inference and learning. Successful outcomes will also lead to a better understanding of the foundations of data science and machine learning in both strategic and non-strategic environments – including emerging concerns like reliability, fairness, privacy and interpretability as data science interacts with society in various ways. The institute will also have broader impacts of strengthening research and educational infrastructure, developing human resources, broadening participation from underrepresented groups, and by connecting theory to science and industry.

The institute will organize activities to engage the community and a diverse group of students at all levels, including introductory workshops for undergraduate research participants, high school student and teacher outreach (through a partnership with the Math Circles of Chicago), and public lectures as part of both our research program and a partnership with the Museum of Science and Industry. The Chicago public institutions that we engage serve a very diverse population, so the outreach, recruitment, and training activities will broaden participation from underrepresented groups. Finally, the institute will have direct engagement with applications and industry through its activities involving Google, other industry partners in the broader Chicago area, and applied data science institutes.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the foundation's intellectual merit and broader impacts review criteria.

Northwestern University

THE GOAL OF THIS FUNDING OPPORTUNITY, "HARNESSING THE DATA REVOLUTION (HDR): TRANSDISCIPLINARY RESEARCH IN PRINCIPLES OF DATA SCIENCE PHASE II", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF21604

47.070 - Computer and Information Science and Engineering

Division of Electrical, Communications and Cyber Systems (ECCS) [NSF]

Division of Computing and Communication Foundations (CCF) [NSF]

Evanston, Illinois 60208-3106 United States

Single Zip Code

Harnessing the Data Revolution (HDR): Transdisciplinary Research in Principles of Data Science Phase II (21-604)

Amendment Since initial award the total obligations have increased 1700% from $171,375 to $3,084,750.