What is he best known for?
The fields of study he is best known for:
- 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.
His most cited work include:
- Approximation Algorithms (3349 citations)
- Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria (1177 citations)
- Algorithmic Game Theory: Computing in Games (1176 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Combinatorics (38.46%)
- Mathematical economics (26.32%)
- Discrete mathematics (24.29%)
What were the highlights of his more recent work (between 2016-2021)?
- Combinatorics (38.46%)
- Matching (13.36%)
- Time complexity (19.03%)
In recent papers he was focusing on the following fields of study:
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.
Between 2016 and 2021, his most popular works were:
- 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)
In his most recent research, the most cited papers focused on:
- 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.
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