Name: Frank Hsu, Clavius Distinguished Professor of Science, Professor of Computer and Information Science, Fordham University, U.S.
Title of talk: Awareness Computing, Combinatorial Fusion, and Cognitive Diversity
Awareness computing has been studied extensively in a variety of awareness contexts such as situation, location, preference, behavior, risk, security and cognition. Computational awareness is a process to understand the mechanisms of awareness in order to realize an awareness computing system. Awareness computing entails acquisition of relevant data content(e.g.: a receptor); extraction, selection, and combination of context features (e.g.: a reactor); and making proper decisions for and characterize possible relations to users (e.g.: a relator).
Combinatorial fusion analysis (CFA), a recently developed algorithmic information fusion paradigm, entails the combination of multiple scoring systems using a rank-score characteristic (RSC) function and the concept of a ¡§cognitive diversity (CD).¡¨ In this talk, we will review recent results in CFA and show how to use the RSC function and cognitive diversity to combine features or fuse decisions. This approach has great potential to provide a unified theory in realizing various intelligent awareness computing systems and to provide a foundation in building the global-scale awareness server (GSAS) system.
Examples are drawn from science, technology, business and society including search engines, virtual screening, target tracking, image recognition, cognitive informatics, affective computing, corporate revenue prediction, and joint decision making.
Frank Hsu is the Clavius Distinguished Professor of Science, a professor of Computer and Information Science, and director of the Laboratory of Informatics and Data Mining (LIDM) at Fordham University in New York City. He was chair of the Dept. of Computer and Information Science, associate dean of the Graduate School of Arts and Sciences at Fordham University, and chair of the Section of Computer and Information Science at the New York Academy of Science. He received an M.S. degree from the University of Texas and a Ph.D. from the University of Michigan. He has been visiting scholar/professor at M.I.T., Taiwan University, Tsing-Hua University (Hsin-Chu, Taiwan), Keio University (IBM Chair Professor), JAIST (Komatsu Chair Professor), and the University of Paris-Sud (and CNRS).
Dr. Hsu¡¦s research interest includes combinatorics, interconnection networks, informatics and computing. He and his colleagues have proposed and developed an algorithmic information fusion paradigm called combinatorial fusion algorithm (CFA). CFA has been used in a variety of domain applications including business intelligence and financial informatics, neuroinformatics and cognitive science, information retrieval, bioinformatics, health informatics, on-line learning, target tracking, and image recognition.
Dr. Hsu is a senior member of IEEE and a Foundation Fellow of the Institute of Combinatorics and Applications. He is a Fellow of the New York Academy of Science (NYAS), the International Institute of Cognitive Informatics and Cognitive Computing (ICIC), and the International Society of Intelligent Biological Medicine (ISIBM). He is the recipient of an IBM Faculty Award in 2012. He has served as Founding Editor and Editor-in-Chief for the Journal of Interconnection Networks and was on the editorial board of IEEE Transactions on Computers, Pattern Recognition Letters, Networks, and International Journal of Foundation of Computer Science. He is on the Editorial Board of the monograph ¡§Health Information Science¡¨ published by Springer and Journal of Advanced Mathematics and Applications by American Scientific Publishers.