![]() ![]() 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 thrusts of the institute will center around the foundations of machine learning, high-dimensional data analysis and inference, and data science and society. ![]() 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. Institute activities will include workshops for undergraduate students, high school teacher workshops, public lectures, and museum exhibit designs. ![]() 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. 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. 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. 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. ![]() TRIPODS Transdisciplinary Rese, HDR-Harnessing the Data Revolu Primary Place of Performance Congressional District: Varun Gupta (Co-Principal Investigator).Lek-Heng Lim (Co-Principal Investigator).Utku Candogan (Co-Principal Investigator).Chao Gao (Principal Investigator) Mladen Kolar (Co-Principal Investigator).Wrote the paper: SN MG YA DB.Institute for Data, Econometrics, Algorithms and Learning (IDEAL) NSF Org:ĮCCS Div Of Electrical, Commun & Cyber SysĪnthony Kuh (703)292-4714 ECCS Div Of Electrical, Commun & Cyber Sys ENG Directorate For Engineering Contributed reagents/materials/analysis tools: SN MG YA DB. The authors have declared that no competing interests exist.Ĭonceived and designed the experiments: SN MG YA DB. The Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois, United States of America,ĭepartment of Physics and the James Franck Institute, The University of Chicago, Chicago, Illinois, United States of America The Institute for Biophysical Dynamics, The University of Chicago, Chicago, Illinois, United States of Americaĭepartment of Statistics, The University of Chicago, Chicago, Illinois, United States of Americaĭepartment of Statistics, The University of Chicago, Chicago, Illinois, United States of America,ĭepartment of Computer Science, The University of Chicago, Chicago, Illinois, United States of America ![]()
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