- Home
- Best Scientists - Computer Science
- Richard M. Karp

Discipline name
D-index
D-index (Discipline H-index) only includes papers and citation values for an examined
discipline in contrast to General H-index which accounts for publications across all
disciplines.
Citations
Publications
World Ranking
National Ranking

Computer Science
D-index
105
Citations
88,505
270
World Ranking
166
National Ranking
105

2009 - SIAM Fellow For contributions to the theory of algorithms and the theory of NP-completeness.

2002 - Fellow of the Institute for Operations Research and the Management Sciences (INFORMS)

1996 - US President's National Medal of Science "For his pioneering research in theoretical computer science and the development of NP-Completeness, a concept having an important role in the theory and the practice of computation.", Awarded by President Clinton in a White House ceremony on July 26, 1996.

1994 - ACM Fellow For his continuing contributions to the theory of algorithms including the development of efficient algorithms for network flow and other combinatorial optimization problems, the identification of polynomial -time computability with the intuitive notion

1992 - Member of the National Academy of Engineering For major contributions to the theory and application of NP-completeness, constructing efficient combinatorial algorithms, and applying probabilistic methods in computer science.

1991 - Fellow of the American Association for the Advancement of Science (AAAS)

1990 - INFORMS John von Neumann Theory Prize

1987 - John von Neumann Lecturer

1985 - Fellow of the American Academy of Arts and Sciences

1985 - A. M. Turing Award For his continuing contributions to the theory of algorithms including the development of efficient algorithms for network flow and other combinatorial optimization problems, the identification of polynomial-time computability with the intuitive notion of algorithmic efficiency, and, most notably, contributions to the theory of NP-completeness. Karp introduced the now standard methodology for proving problems to be NP-complete which has led to the identification of many theoretical and practical problems as being computationally difficult.

1980 - Member of the National Academy of Sciences

- Algorithm
- Computer network
- Statistics

Richard M. Karp mostly deals with Discrete mathematics, Combinatorics, Algorithm, Theoretical computer science and Distributed computing. His Discrete mathematics study incorporates themes from Tree traversal, Upper and lower bounds, Graph and Computation. His Combinatorics research is multidisciplinary, relying on both Linear programming and Travelling salesman problem.

Richard M. Karp has included themes like Mathematical economics, Complexity class, Matroid and Integer programming in his Travelling salesman problem study. His Algorithm research incorporates elements of Mathematical optimization and Probabilistic analysis of algorithms. His Distributed computing research is multidisciplinary, incorporating elements of Overlay network and Computer network, Server.

- Reducibility Among Combinatorial Problems. (6546 citations)
- A scalable content-addressable network (6477 citations)
- An $n^{5/2} $ Algorithm for Maximum Matchings in Bipartite Graphs (2331 citations)

Richard M. Karp focuses on Combinatorics, Algorithm, Discrete mathematics, Theoretical computer science and Upper and lower bounds. His study ties his expertise on Parallel algorithm together with the subject of Combinatorics. Parallel algorithm is a subfield of Parallel computing that Richard M. Karp explores.

His research integrates issues of Mathematical optimization and Probabilistic analysis of algorithms in his study of Algorithm. His work deals with themes such as Function and Linear programming, which intersect with Discrete mathematics. He interconnects Randomized algorithm, Computation and Set in the investigation of issues within Theoretical computer science.

- Combinatorics (25.88%)
- Algorithm (24.71%)
- Discrete mathematics (19.41%)

- Algorithm (24.71%)
- Set (7.35%)
- Combinatorics (25.88%)

His primary areas of investigation include Algorithm, Set, Combinatorics, Theoretical computer science and Matching. Richard M. Karp focuses mostly in the field of Algorithm, narrowing it down to topics relating to Communication channel and, in certain cases, Asymptotically optimal algorithm and Flow network. His biological study spans a wide range of topics, including Discrete mathematics, Upper and lower bounds and Sorting.

His research in Theoretical computer science intersects with topics in Machine learning, Task and Graph. His Matching study combines topics in areas such as Correctness, Pairwise comparison, Topology and Integer programming. The study incorporates disciplines such as Matroid, Mathematical economics, Complexity class, Travelling salesman problem and Gene regulatory network in addition to Integer programming.

- Reducibility Among Combinatorial Problems (2006 citations)
- Conserved patterns of protein interaction in multiple species (689 citations)
- Efficient algorithms for detecting signaling pathways in protein interaction networks. (255 citations)

- Algorithm
- Computer network
- Statistics

Richard M. Karp mainly investigates Genetics, Matching, Computational biology, Algorithm and Protein Interaction Networks. His Matching research includes themes of Set, Topology, Travelling salesman problem, Sequence and Integer programming. His studies deal with areas such as Matroid, Turing machine, Flow network, Mathematical economics and Complexity class as well as Integer programming.

His study in Computational biology is interdisciplinary in nature, drawing from both Genetic analysis, Bacterial protein, Bacteria, Yeast and Protein sequencing. His work deals with themes such as Smith–Waterman algorithm, Nucleotide, Channel capacity and Random graph, which intersect with Algorithm. Richard M. Karp integrates many fields, such as Protein network and Theoretical computer science, in his works.

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.

Reducibility Among Combinatorial Problems

Richard M. Karp.

Journal of Symbolic Logic **(2010)**

20734 Citations

A scalable content-addressable network

Sylvia Ratnasamy;Paul Francis;Mark Handley;Richard Karp.

acm special interest group on data communication **(2001)**

10946 Citations

An $n^{5/2} $ Algorithm for Maximum Matchings in Bipartite Graphs

John E. Hopcroft;Richard M. Karp.

SIAM Journal on Computing **(1973)**

3973 Citations

Theoretical improvements in algorithmic efficiency for network flow problems

Jack Edmonds;Richard M. Karp.

Combinatorial optimization - Eureka, you shrink! **(2003)**

3387 Citations

Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems

Jack Edmonds;Richard M. Karp.

Journal of the ACM **(1972)**

3018 Citations

LogP: towards a realistic model of parallel computation

David Culler;Richard Karp;David Patterson;Abhijit Sahay.

acm sigplan symposium on principles and practice of parallel programming **(1993)**

2450 Citations

Efficient randomized pattern-matching algorithms

Richard M. Karp;Michael O. Rabin.

Ibm Journal of Research and Development **(1987)**

1861 Citations

The Traveling-Salesman Problem and Minimum Spanning Trees

Michael Held;Richard M. Karp.

Operations Research **(1970)**

1858 Citations

A Dynamic Programming Approach to Sequencing Problems

Michael Held;Richard M. Karp.

Journal of The Society for Industrial and Applied Mathematics **(1962)**

1787 Citations

Discovering local structure in gene expression data: the order-preserving submatrix problem.

Amir Ben-Dor;Benny Chor;Richard M. Karp;Zohar Yakhini.

Journal of Computational Biology **(2003)**

1608 Citations

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

Contact us

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:

Tel Aviv University

BitRipple

Tel Aviv University

University of California, Berkeley

University of California, Los Angeles

Institute for Advanced Study

Columbia University

University of California, San Diego

University of California, Riverside

University of Southern California

Duke University

Google (United States)

ETH Zurich

Royal Institute of Technology

Arizona State University

University of Cincinnati

École Polytechnique Fédérale de Lausanne

University of Oviedo

Nagoya University

University of Arizona

Osaka Metropolitan University

KU Leuven

Lamont-Doherty Earth Observatory

Ruhr University Bochum

Harvard University

University of Manchester

Something went wrong. Please try again later.