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This presentation will discuss a research agenda for information fusion with hard or physics-based sensor and soft or human-based observations. The primary research thrusts addressed are framed around the major functional components of the JDL Fusion Process which include: Source Characterization of Soft Data input streams including human observations; Common Referencing and Alignment of Hard and Soft Data; Generalized Data Association Strategies and Algorithms for Hard and Soft Data Association; and Robust Estimation Methods that exploit associated Hard and Soft Data.
An important problem in this framework is Graph Association or merging many graphs that collectively describe a set of possibly repetitive entities and relationships into a single graph that contains unique entities and relationships. As a form of data association, graph association can be used to identify when two sensors are observing the same object so information from both sensors can be combined and analyzed in a meaningful and consistent way. Our research contribution is to formulate graph association as a binary integer program and introduce a heuristic for solving multiple graph association using a Lagrangian relaxation to address issues with between-graph transitivity requirements. We further expand on this work by implementing a special case of node association for BIG DATA in a Map-Reduce framework that is easily distributed across a cluster of computers. Distribution allows the heuristic to address the real-time and large data requirements of data association. Processor scaling results on Amazon EC2 and UB's Hadoop cluster will be presented.
Rakesh Nagi is Professor of Industrial and Systems Engineering at the University at Buffalo (SUNY). He received his Ph.D. (1991) and M.S. (1989) degrees in Mechanical Engineering from the University of Maryland at College Park, while he worked at the Institute for Systems Research and INRIA, France, and B.E. (1987) degree in Mechanical Engineering from University of Roorkee (now IIT-R), India.
He is a recipient of IIE Fellow Award (2010), UBs “Sustained Achievement Award" in recognition of outstanding achievements in scholarly activity (2009), Business First of Buffalos “40 under Forty" award (2004), SME's Milton C. Shaw Outstanding Young Manufacturing Engineer Award (1999), IIE's Outstanding Young Industrial Engineer Award in Academia (1999), and National Science Foundation's CAREER Award (1996). His papers have been published in journals including IIE Transactions, International Journal of Production Research, Journal of Manufacturing Systems, International Journal of Flexible Manufacturing Systems, Journal of Intelligent Manufacturing, Computers in Industry, Computer Integrated Manufacturing Systems, Management Science, Operations Research, Naval Research Logistics, European Journal of Operational Research, Annals of Operations Research, Computers and Operations Research, Computers and Industrial Engineering, and ASME and IEEE Transactions. Dr. Nagi's established academic interests lie in manufacturing systems, facilities design, production management, applied operations research, supply chain management, and agile and information enabled manufacturing. More recently he has been working on information fusion, intelligence applications, social networks and military operations research.