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- Vijay V. Vazirani

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
58
Citations
27,009
192
World Ranking
2323
National Ranking
1249

2011 - Fellow of John Simon Guggenheim Memorial Foundation

2005 - ACM Fellow For contributions to optimization and approximation algorithms.

- Algorithm
- Statistics
- Algebra

Vijay V. Vazirani mostly deals with Approximation algorithm, Discrete mathematics, Combinatorics, Theoretical computer science and Mathematical optimization. His Approximation algorithm research includes elements of Mathematical proof, Management science, Schema, Greedy algorithm and Linear programming. His Linear programming study combines topics in areas such as Mathematical economics and Game theory.

His work deals with themes such as Facility location problem, Random number generation, Algebra and Turing machine, which intersect with Discrete mathematics. His Theoretical computer science research includes themes of Algorithm engineering, Algorithmics, Computational geometry and 3-dimensional matching. His studies deal with areas such as Time complexity and Bipartite graph as well as Mathematical optimization.

- Approximation Algorithms (3349 citations)
- Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria (1177 citations)
- Algorithmic Game Theory: Computing in Games (1176 citations)

His primary scientific interests are in Combinatorics, Mathematical economics, Discrete mathematics, Algorithm and Approximation algorithm. His study in Combinatorics is interdisciplinary in nature, drawing from both Matching and Parallel algorithm. The concepts of his Mathematical economics study are interwoven with issues in Price discrimination and Mathematical optimization.

His Discrete mathematics research is multidisciplinary, incorporating perspectives in Computational complexity theory, Multi-commodity flow problem and Graph. His Algorithm research incorporates elements of Open problem and Graph. His studies in Approximation algorithm integrate themes in fields like Linear programming, Combinatorial optimization, Schema and Steiner tree problem.

- Combinatorics (38.46%)
- Mathematical economics (26.32%)
- Discrete mathematics (24.29%)

- Combinatorics (38.46%)
- Matching (13.36%)
- Time complexity (19.03%)

Vijay V. Vazirani mainly focuses on Combinatorics, Matching, Time complexity, Incentive compatibility and Mathematical optimization. His primary area of study in Combinatorics is in the field of Graph. His study in Matching is interdisciplinary in nature, drawing from both Maximum flow problem, Parallel algorithm, Open problem and Planar graph.

His Parallel algorithm study typically links adjacent topics like Discrete mathematics. Vijay V. Vazirani interconnects Mathematical proof, Industrial organization, School choice and Strategic dominance in the investigation of issues within Incentive compatibility. His Mathematical optimization study integrates concerns from other disciplines, such as Mathematical economics and Selection.

- Convex Program Duality, Fisher Markets, and Nash Social Welfare (55 citations)
- Nash social welfare for indivisible items under separable, piecewise-linear concave utilities (36 citations)
- Planar Graph Perfect Matching Is in NC (12 citations)

- Algorithm
- Statistics
- Algebra

His primary scientific interests are in Time complexity, Combinatorics, Mathematical optimization, Mathematical economics and Stable marriage problem. His work deals with themes such as Scheduling, Open problem, Submodular set function and Minification, which intersect with Time complexity. His Combinatorics research integrates issues from Matching, Parallel algorithm and Face.

His biological study spans a wide range of topics, including Representation, Type, Planar graph, Minimum weight and Point. The study incorporates disciplines such as Matching, Incentive compatibility and Reduction in addition to Mathematical optimization. His Mathematical economics research is multidisciplinary, relying on both Maximization, Duality, Linear matrix inequality and Convex analysis, Convex optimization.

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.

Approximation Algorithms

Vijay V. Vazirani.

**(2001)**

5476 Citations

Approximation Algorithms

Vijay V. Vazirani.

**(2001)**

5476 Citations

Algorithmic Game Theory: Computing in Games

Noam Nisan;Tim Roughgarden;Eva Tardos;Vijay V. Vazirani.

**(2007)**

1920 Citations

Algorithmic Game Theory: Computing in Games

Noam Nisan;Tim Roughgarden;Eva Tardos;Vijay V. Vazirani.

**(2007)**

1920 Citations

Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria

Noam Nisan;Tim Roughgarden;Eva Tardos;Vijay V. Vazirani.

**(2007)**

1916 Citations

Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria

Noam Nisan;Tim Roughgarden;Eva Tardos;Vijay V. Vazirani.

**(2007)**

1916 Citations

NP is as easy as detecting unique solutions

L. G. Valiant;V. V. Vazirani.

Theoretical Computer Science **(1986)**

1805 Citations

NP is as easy as detecting unique solutions

L. G. Valiant;V. V. Vazirani.

Theoretical Computer Science **(1986)**

1805 Citations

An O(v|v| c |E|) algoithm for finding maximum matching in general graphs

Silvio Micali;Vijay V. Vazirani.

foundations of computer science **(1980)**

1284 Citations

An O(v|v| c |E|) algoithm for finding maximum matching in general graphs

Silvio Micali;Vijay V. Vazirani.

foundations of computer science **(1980)**

1284 Citations

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