Planning Grant: I/UCRC for Center for Dynamic Data Analytics Site at the University of Virginia

University Of Virginia Main Campus, Charlottesville VA

Investigators

Abstract

The University of Virginia (UVA) is planning to join the Center for Dynamic Data Analytics, an existing multi-university Industry/University Cooperative Research Center (I/UCRC) which is currently comprised of Rutgers University (lead institution) and Stony Brook University. This award provides UVA with the support from the NSF for exploring the feasibility of establishing this new site. The planning grant will be used to plan a joint industry and university research agenda, to organize and attend the meetings with potential industry members and the existing sites, and to host a planning meeting that will be the center point of the effort to articulate the vision for the site to potential members. The principal industry domains for UVA/CDDA research are: (1) Finance and banking, including financial markets and electronic trading, systemic risk, and data analytics for regulators; (2) Internet analytics, including marketing and the Internet of Things; (3) Advanced manufacturing, including data-driven approaches to automation, human factors, process improvement, and prognostics; (4) Cyberphysical systems, including cybersecurity of physical systems and autonomous systems. Together these domains constitute a portion of the economy that is both substantial and increasing. The primary mission of the UVA site of CDDA is to perform research on data analytics to support decision making in industry and government. The focus is on analysis of data sets distinguished by their velocity, variety, volume, complexity, and other features commonly associated with Big Data. The UVA site of CDDA will pursue a research agenda that complements that of the existing sites and features an integration of control, decision, and systems modeling concepts with statistical methods, machine learning and pattern recognition. Areas of concentration include behavioral and preference modeling, state-based models, reinforcement learning, secure computation and data privacy, and data-driven approaches to cybersecurity. A principal distinguishing characteristic of the UVA site research agenda is an emphasis on prescriptive modeling and understanding the collection and use of data in the context of decision making in complex systems.