Data Science is rapidly evolving as an essential interdisciplinary field, where advances often result from a combination of ideas from several disciplines. New types of data have emerged and present tremendous complexities and challenges that require a novel way of interdisciplinary thinking. The Texas A&M Research Institute for Foundations of Interdisciplinary Data Science (FIDS) will bring together researchers from five disciplinary areas, Statistics, Electrical Engineering, Mathematics, Computer Science and Industrial Engineering, to conduct research on the foundations of data science motivated by problems arising in bioinformatics, the energy arena, power systems, and transportation systems. The Institute for Foundations of Interdisciplinary Data Science will be well-positioned to develop rigorous theories, novel methodologies, and efficient computational techniques to solve data challenges in many application domains.

Modern large datasets are extremely complex and finding answers to seemingly simple questions often turns into an intractable problem. To address these challenges, FIDS will advance the foundations of data science through research on modeling complex data and developing related theory and algorithms. Development of efficient methods to identify low-dimensional structures in these high-dimensional complex data will be the key strategy to recovering high-dimensional signals with related uncertainties. Novel data-analysis models and algorithms will be developed for representation learning, information extraction, and knowledge discovery from complex data to enable better decision making. To complement the research effort, FIDS will educate and train students and postdoctoral fellows in areas at the interface of engineering, mathematics, and statistics. Targeted outreach programs will be developed to increase the pool of women and underrepresented minorities who pursue data-science careers. An external engagement program will be designed to facilitate collaborations with domain scientists and external data scientists. These programs will help to develop the intellectual foundation for a new generation of scientists poised to make novel breakthroughs in this exciting new field.

This project is part of the National Science Foundation's Harnessing the Data Revolution (HDR) Big Idea activity.

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.

Agency
National Science Foundation (NSF)
Institute
Division of Computer and Communication Foundations (CCF)
Application #
1934904
Program Officer
Huixia Wang
Project Start
Project End
Budget Start
2019-10-01
Budget End
2022-09-30
Support Year
Fiscal Year
2019
Total Cost
$458,174
Indirect Cost
Name
Texas A&M University Main Campus
Department
Type
DUNS #
City
College Station
State
TX
Country
United States
Zip Code
77845