- Home
- Top Scientists - Engineering and Technology
- Dimitri P. Bertsekas

Discipline name
H-index
Citations
Publications
World Ranking
National Ranking

Mathematics
H-index
85
Citations
95,159
219
World Ranking
47
National Ranking
29

Engineering and Technology
H-index
96
Citations
121,937
257
World Ranking
39
National Ranking
21

2018 - INFORMS John von Neumann Theory Prize

2015 - Dantzig Prize, by the Society for Industrial and Applied Mathematics (SIAM) and the Mathematical Optimization Society (MOS)

2014 - Khachiyan Prize of the INFORMS Optimization Society

2014 - Richard E. Bellman Control Heritage Award

2001 - Member of the 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.

- Mathematical optimization
- Computer network
- Mathematical analysis

Dimitri P. Bertsekas focuses on Mathematical optimization, Dynamic programming, Rate of convergence, Convex optimization and Algorithm. Much of his study explores Mathematical optimization relationship to Shortest path problem. His Dynamic programming research is multidisciplinary, relying on both Stochastic programming, Computation, Optimal control and Reactive programming.

His research integrates issues of Orthant, Combinatorics, Penalty method and Hessian matrix in his study of Rate of convergence. His research in Convex optimization tackles topics such as Subgradient method which are related to areas like Convergence, Convex function and Differentiable function. Dimitri P. Bertsekas combines subjects such as Assignment problem, Computer network programming, Numerical analysis and Dual with his study of Algorithm.

- Nonlinear Programming (11151 citations)
- Dynamic Programming and Optimal Control (8194 citations)
- Data networks (5967 citations)

Dimitri P. Bertsekas spends much of his time researching Mathematical optimization, Dynamic programming, Algorithm, Convergence and Shortest path problem. By researching both Mathematical optimization and Markov decision process, he produces research that crosses academic boundaries. Dimitri P. Bertsekas has included themes like Stochastic programming, Stochastic control, Computation, Decision problem and Reinforcement learning in his Dynamic programming study.

The various areas that Dimitri P. Bertsekas examines in his Computation study include Distributed algorithm and Theoretical computer science. In his research on the topic of Algorithm, Distributed computing is strongly related with Asynchronous communication. His Convergence research includes elements of Telecommunications network and Iterative method.

- Mathematical optimization (57.65%)
- Dynamic programming (25.88%)
- Algorithm (20.00%)

- Mathematical optimization (57.65%)
- Dynamic programming (25.88%)
- Function (7.06%)

Dimitri P. Bertsekas mainly focuses on Mathematical optimization, Dynamic programming, Function, Reinforcement learning and Shortest path problem. Dimitri P. Bertsekas does research in Mathematical optimization, focusing on Subgradient method specifically. In his works, Dimitri P. Bertsekas performs multidisciplinary study on Dynamic programming and Markov decision process.

His Function research integrates issues from State and Heuristic. His study in Reinforcement learning is interdisciplinary in nature, drawing from both Theoretical computer science, Artificial neural network, Aggregate and Algorithm, Computation. Dimitri P. Bertsekas has researched Shortest path problem in several fields, including Discrete mathematics, Bounded function and Minimax.

- Constrained Optimization and Lagrange Multiplier Methods (2914 citations)
- Convex Optimization Algorithms (409 citations)
- Incremental Gradient, Subgradient, and Proximal Methods for Convex Optimization: A Survey. (317 citations)

- Mathematical optimization
- Computer network
- Mathematical analysis

His scientific interests lie mostly in Mathematical optimization, Dynamic programming, Rate of convergence, Convex optimization and Subgradient method. His Mathematical optimization study integrates concerns from other disciplines, such as Convergence, Stochastic approximation and Algorithm. The study incorporates disciplines such as Reactive programming and Reinforcement learning in addition to Dynamic programming.

The Reactive programming study combines topics in areas such as Functional logic programming and Programming domain. His studies in Rate of convergence integrate themes in fields like Variational inequality, Temporal difference learning and Iterative method. His research in Convex optimization intersects with topics in Linear matrix inequality and Projection.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Nonlinear Programming

Dimitri Bertsekas.

**(1995)**

16027 Citations

Dynamic Programming and Optimal Control

Dimitri P. Bertsekas.

**(1995)**

12378 Citations

Data Networks

Dimitri Bertsekas;Robert Gallager.

**(1986)**

11206 Citations

Parallel and Distributed Computation: Numerical Methods

Dimitri P. Bertsekas;John N. Tsitsiklis.

**(1989)**

8100 Citations

Parallel and distributed computation

D.P. Bertsekas;J.N. Tsitsiklis.

**(1989)**

8098 Citations

Neuro-dynamic programming

Dimitri P. Bertsekas;John N. Tsitsiklis.

**(1996)**

6637 Citations

Neuro-dynamic programming: an overview

D.P. Bertsekas;J.N. Tsitsiklis.

conference on decision and control **(1995)**

5776 Citations

Constrained Optimization and Lagrange Multiplier Methods

Dimitri P. Bertsekas.

**(1982)**

5070 Citations

Dynamic Programming and Stochastic Control

D. P. Bertsekas;Chelsea C. White.

systems man and cybernetics **(1977)**

3997 Citations

On the Douglas-Rachford splitting method and the proximal point algorithm for maximal monotone operators

Jonathan Eckstein;Dimitri P. Bertsekas.

Mathematical Programming **(1992)**

2503 Citations

Profile was last updated on December 6th, 2021.

Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).

The ranking h-index is inferred from publications deemed to belong to the considered discipline.

If you think any of the details on this page are incorrect, let us know.

Contact us

Boston University

University of Washington

University of California, Los Angeles

MIT

National Technical University of Athens

Arizona State University

Indian Institute of Technology Bombay

Instituto Superior Técnico

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Something went wrong. Please try again later.