Katehakis, Michael N. (Rutgers University)

Michael N. Katehakis

Michael N. Katehakis
Rutgers University

100 Rockafeller Rd. Rm. 5147

Piscataway, NJ 08854

Email: mnk@rutgers.edu
Website: http://www.rci.rutgers.edu/~mnk/

Background:

  • Ph.D., Operations Research, Columbia University, 1980
  • M.Sc., Operations Research, Columbia University, 1976
  • Bachelors, National and Kapodistrian University of Athens, Greece

Dr. Katehakis is a Professor in the Management Science and Information Systems Department at Rutgers University and past chair of the Department (2011-2014). He holds a courtesy appointment in Rutgers' New Brunswick Department of Mathematics Graduate Faculty, and he is a member of DIMACS the Center for Discrete Mathematics and Theoretical Computer Science, he is a Primary Investigator of CDDA the Rutgers Center for Dynamic Data Analytics, and a member of RUTCOR, the Rutgers Center for Operations Research.

Much of his work has been on the interaction between optimization and statistical inference. Specific research interests include Stochastic Models, Dynamic Programming, Statistical Analysis and their application to Operations Management problems of pricing, production planning, inventory control, supply chains and scheduling. Many of these subjects are now known as Business Analytics a rapidly developing field at Google and at IBM.

Dr. Katehakis is a Professor in the Management Science and Information Systems Department at Rutgers University and past chair of the Department (2011-2014). He holds a courtesy appointment in Rutgers' New Brunswick Department of Mathematics Graduate Faculty, and he is a member of DIMACS the Center for Discrete Mathematics and Theoretical Computer Science, he is a Primary Investigator of CDDA the Rutgers Center for Dynamic Data Analytics, and a member of RUTCOR, the Rutgers Center for Operations Research.
Much of his work has been on the interaction between optimization and statistical inference. Specific research interests include Stochastic Models, Dynamic Programming, Statistical Analysis and their application to Operations Management problems of pricing, production planning, inventory control, supply chains and scheduling. Many of these subjects are now known as Business Analytics a rapidly developing field at Google and at IBM.