Distinguished Professor and Department Chair
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.
He has co-authored many papers, with distinguished leaders in his field including: Cy Derman, Herbert E. Robbins, Sheldon M. Ross, Arthur F. Veinott Jr., Jerzy Filar, Uriel Rothblum, and Govindarajulu Z. with whom he won the 1992 Wolfowitz Prize for the paper "Dynamic allocation in survey sampling''. His work has been published in top journals and it has been funded by grants from the NSF and the AFOSR. Many of his Ph.D. students and their academic descendants are listed in The Mathematics Genealogy Project.
Professor Katehakis joined the Rutgers University faculty in 1989 after receiving his doctorate in Operations Research at Columbia University under the supervision of Cyrus Derman, and after being a faculty member at SUNY Stony Brook and at the Technical University of Crete. In addition, professor Katehakis was a member of the technical staff at the Operations Research Center of Bell - Laboratories, West Long Branch and a consultant at Brookhaven National Laboratory and he has held visiting appointments and taught at Columbia University, Stanford University and the National and Kapodistrian University of Athens, Greece.
Prof. Michael N. Katehakis is a Fellow of the Institute for Operations Research and the Management Sciences (INFORMS), an Elected Member of the International Statistical Institute (ISI) and a Senior Member of the Institute of Electrical and Electronics Engineers (IEEE).
Ph.D., Columbia University; Operations Research
M.Phil., Columbia University; Operations Research
M. A., University of South Florida, Statistics
M.Sc., Columbia University; Mathematical Methods in Engineering and Operations Research
Name: Varzgani, Nilofar
Graduation Date: 2017/October
Thesis Title: New Dynamic Optimization Models for Tax Loss Valuation and Sourcing Problems
Name: Gilani, Wajahat
Graduation Date: 2016/May
Thesis Title: Optimal Execution of Real Options in illiquid and Incomplete Markets
Name: Smit, Laurens
Graduation Date: 2014/May
Thesis Title: On Successive Lumping of Large Scale Systems
Name: Puranam, Srinivasa (Karti)
Graduation Date: 2010/October
Thesis Title: Stochastic Analysis of Bidding in Sequential Auctions and Related Problems.
Name: Shi, Junmin
Graduation Date: 2010/October
Thesis Title: Make-to-Stock Production-Inventory Systems with Compound Poisson Demands, Constant Continuous Replenishment and Lost Sales.
(Co-directed with B. Melamed)
Name: Chen, Wen
Graduate Date: 2008
Thesis Title: New models and solutions for stochastic optimization for R&D and transportation problems
Name: Zhou, Bin
Graduation Date: 2007/May
Thesis Title: On Optimal Pricing and Ordering in Supply Chain Management
(Co-directed with Yao Zhao)
Name: Elkins, Timothy
Graduation Date: 2003/May
Thesis Title: Multiple Criteria/Multiple Objective and Dynamic Data Envelopment Analysis with the Freight Service Business.
Name: Gursoy, Kemal
Graduation Date: 1997/October
Thesis Title: Branch and Bound Methods for Sequentially Choosing Some Among Several Competing Projects.
Name: Burnetas, Apostolos
Graduation Date: 1993/October
Thesis Title: On Adaptive Estimation and Control for Markovian Decision Processes.