Prakash P Shenoy
- Ronald G. Harper Distinguished Professor of Artificial Intelligence
Prakash P. Shenoy is the Ronald G. Harper Distinguished Professor of Artificial Intelligence in Business, University of Kansas at Lawrence. He received a B.Tech. in Mechanical Engineering from the Indian Institute of Technology, Bombay, India, in 1973, and an M.S. and a Ph.D. in Operations Research from Cornell University in 1975 and 1977, respectively.
His research interests are in the areas of artificial intelligence and decision sciences. He is the inventor of valuation-based systems, an abstract framework for knowledge representation and inference that includes Bayesian probabilities, Dempster-Shafer belief functions, Spohn's kappa calculus, Zadeh's possibility theory, propositional logic, optimization, solving systems of equations, database retrieval, and other domains. He is also the co-author (with G. Shafer) of the so-called Shenoy-Shafer architecture for computing marginals of joint distributions using local computation. He has published many articles on the management of uncertainty in expert systems, on decision analysis, and on the mathematical theory of games. His articles have appeared in journals such as Operations Research, Management Science, International Journal of Game Theory, Artificial Intelligence, and International Journal of Approximate Reasoning. He has received several research grants/contracts from the Database and Expert Systems (DES), and Decision, Risk and Management Science (DRMS) programs of the National Science Foundation, the Research Opportunities in Auditing program of the Peat Marwick Main Foundation, the Higher Education Academic Development Donations program of Apple Computer, Inc., the Information Sciences Department of Hughes Research Laboratories, Space Dynamics Laboratory of Utah State University, Information Extraction and Transport, Inc., Science Applications International Corp., Sparta, Inc., and Raytheon Missile Systems, Inc.
He serves as an Associate Editor of International Journal of Approximate Reasoning, and as an ad-hoc referee for over 30 journals and conferences in Artificial Intelligence and Management Science/Operations Research. He has served as an Area Editor for International Journal of Fuzziness and Knowledge-Based Systems, as an Associate Editor of Operations Research, as an Associate Editor of Management Science, as Program Co-Chair of the Thirteenth Conference on Uncertainty in Artificial Intelligence held at Brown University, Providence, 1997, and as Conference Chair of the Fourteenth Conference on Uncertainty in Artificial Intelligence held at University of Wisconsin-Madison in 1998.
His teaching interests are in the areas of uncertain reasoning, decision analysis, and statistics. He has taught undergraduate and graduate courses on linear programming, non-linear programming, game theory, management information systems, decision support systems, uncertain reasoning, probability, statistics, multivariate statistics, supply chain modeling & optimization, and data analysis & forecasting. He has served on doctoral dissertation committees of forty PhD students in Management Science, Marketing, Accounting, Economics, Electrical Engineering and Computer Science, Geography, Civil Engineering, and Philosophy, ten as chairperson. He has received the Outstanding Mentor Award from the Association of Business Doctoral Students five times, an Excellence in Teaching Award from the Center for Teaching Excellence, and an Outstanding Mentor Award from the Graduate and Professional Association of the University of Kansas.
In Summer 2012, with the help of Dean Neeli Bendapudi and his colleagues in Decision Sciences, Marketing, and Finance, he formed the Center for Business Analytics Research (CBAR). In Fall 2013, DST Systems, Inc. joined CBAR as a founding corporate sponsor. In Spring 2015, AIG, Inc. joined CBAR as a corporate sponsor. He currently serves as the academic faculty Director of CBAR.
- uncertainty in artificial intelligence
- knowledge-based systems
- decision analysis
- game theory
- uncertainty in artificial intelligence
- decision analysis and game theory
- probability and statistics
- supply chain modeling
- data analysis and forecasting