This program seeks to develop and apply algorithmic methods for the control of systems characterized by the need to make real-time decisions based on data arriving in high volume. To this end, the program will create collaborations between two groups of experts: workers in domains of physical science, engineering and societal systems involving real-time discovery and inference, and mathematical and computational scientists with the tools required to attack the decision-theoretic problems arising in these domains. The program will focus in particular on astronomical observation, earthquake early warning, transportation networks, online matching markets and smart energy grids. Theoretical advances in streaming algorithms, distributed algorithms, machine learning, database management,  analysis of heterogeneous, noisy and unformatted high-dimensional data, information theory, control theory, and optimization will be required to meet the challenges of these and related application domains.  

This program is supported in part by the Gordon and Betty Moore Foundation.


Long-Term Participants (including Organizers)

Ana Bušić (INRIA and École Normale Supérieure Paris)
Bruce Hajek (University of Illinois at Urbana-Champaign)
Mike Luby (International Computer Science Institute)
R. Srikant (University of Illinois at Urbana-Champaign)
Le Xie (Texas A&M University)

Research Fellows

Visiting Graduate Students and Postdocs