Dimitri P. Bertsekas undergraduate studies were in engineering at the National Technical University of Athens, Greece. He obtained his MS in electrical engineering at the George Washington University, Wash. DC in 1969, and his Ph.D. in system science in 1971 at the Massachusetts Institute of Technology.

Dr. Bertsekas has held faculty positions with the Engineering-Economic Systems Dept., Stanford University (1971-1974) and the Electrical Engineering Dept. of the University of Illinois, Urbana (1974-1979). Since 1979 he has been teaching at the Electrical Engineering and Computer Science Department of the Massachusetts Institute of Technology (M.I.T.), where he is currently McAfee Professor of Engineering. He has held editorial positions in several journals. His research at M.I.T. spans several fields, including optimization, control, large-scale computation, and data communication networks, and is closely tied to his teaching and book authoring activities. He has written numerous research papers, and fifteen books, several of which are used as textbooks in MIT classes.

Professor Bertsekas was awarded the INFORMS 1997 Prize for Research Excellence in the Interface Between Operations Research and Computer Science for his book "Neuro-Dynamic Programming" (co-authored with John Tsitsiklis), the 2000 Greek National Award for Operations Research, the 2001 ACC John R. Ragazzini Education Award, the 2009 INFORMS Expository Writing Award, the 2014 ACC Richard E. Bellman Control Heritage Award for "contributions to the foundations of deterministic and stochastic optimization-based methods in systems and control," and the 2014 Khachiyan Prize for Life-Time Accomplishments in Optimization. In 2001, he was elected to the United States National Academy of Engineering for "pioneering contributions to fundamental research, practice and education of optimization/control theory, and especially its application to data communication networks."

Dr. Bertsekas' recent books are "Introduction to Probability: 2nd Edition" (2008), "Convex Optimization Theory" (2009), "Dynamic Programming and Optimal Control, Vol. II: Approximate Dynamic Programming" (2012), and "Abstract Dynamic Programming" (2013), all published by Athena Scientific.

Besides his professional activities, Professor Bertsekas is interested in travel, portrait, and landscape photography. His pictures have been exhibited on several occasions at M.I.T., and can also be accessed from his www site.

Complete List of Publications, Research Papers.

Professor Bertsekas is the author of

*Dynamic Programming and Stochastic Control,*Academic Press, 1976,*Constrained Optimization and Lagrange Multiplier Methods,*Academic Press, 1982, and Athena Scientific, 1996,*Dynamic Programming: Deterministic and Stochastic Models,*Prentice-Hall, 1987,*Linear Network Optimization: Algorithms and Codes,*MIT Press, 1991,*Dynamic Programming and Optimal Control, Vols. I and II,**Nonlinear Programming,*Athena Scientific, 1995 (2nd Edition, 1999),*Network Optimization: Continuous and Discrete Models,**Convex Optimization Theory,*Athena Scientific, May 2009.*Abstract Dynamic Programming,*Athena Scientific, April 2013.

and co-author of

*Stochastic Optimal Control: The Discrete-Time Case,*Academic Press, 1978, and Athena Scientific, 1996,*Data Networks,*Prentice-Hall, 1987 (2nd Ed. 1991),*Parallel and Distributed Computation: Numerical Methods,*Prentice-Hall, 1989, and Athena Scientific, 1997,*Neuro-Dynamic Programming,*Athena Scientific, 1996,*Introduction to Probability,*Athena Scientific, 2002; 2nd Edition, 2008.*Convex Analysis and Optimization,*Athena Scientific, March 2003.

Professor Bertsekas has done research in the areas of

- linear and nonlinear programming
- network optimization
- dynamic and neuro-dynamic programming
- estimation and control of stochastic systems
- neural networks
- parallel and distributed computation
- data communication networks

and has written numerous research papers in each of these areas.

Professor Bertsekas teaches graduate courses at the Massachusetts Institute of Technology in

- nonlinear programming,
- dynamic programming,
- data communication networks,
- convex analysis and optimization,
- probabilistic systems analysis,