What is he best known for?
The fields of study he is best known for:
- Algorithm
- Computer network
- Programming language
His scientific interests lie mostly in Combinatorics, Discrete mathematics, Approximation algorithm, Time complexity and Theoretical computer science.
He has researched Combinatorics in several fields, including Matching, Computational complexity theory and Bin packing problem.
His research integrates issues of Multi-commodity flow problem, Metric and Relaxation in his study of Discrete mathematics.
His Approximation algorithm study integrates concerns from other disciplines, such as Linear programming, Routing, Bounded function and Disjoint sets.
The concepts of his Time complexity study are interwoven with issues in Completion time, If and only if and Graph.
Sanjeev Khanna focuses mostly in the field of Theoretical computer science, narrowing it down to matters related to Contrast and, in some cases, Online computation, Sequence, Data type, Group and Value.
His most cited work include:
- Why and Where: A Characterization of Data Provenance (1095 citations)
- Space-efficient online computation of quantile summaries (443 citations)
- Complexity classifications of Boolean constraint satisfaction problems (389 citations)
What are the main themes of his work throughout his whole career to date?
Sanjeev Khanna mostly deals with Combinatorics, Discrete mathematics, Approximation algorithm, Upper and lower bounds and Mathematical optimization.
His Combinatorics research is multidisciplinary, incorporating elements of Matching and Bounded function.
His study looks at the relationship between Discrete mathematics and fields such as Multi-commodity flow problem, as well as how they intersect with chemical problems.
Sanjeev Khanna studied Approximation algorithm and Computational complexity theory that intersect with Graph theory.
His Mathematical optimization study incorporates themes from Mathematical economics and Scheduling.
His Algorithm research is multidisciplinary, incorporating perspectives in Simple and Theoretical computer science.
He most often published in these fields:
- Combinatorics (40.26%)
- Discrete mathematics (33.00%)
- Approximation algorithm (21.12%)
What were the highlights of his more recent work (between 2014-2021)?
- Combinatorics (40.26%)
- Discrete mathematics (33.00%)
- Upper and lower bounds (14.19%)
In recent papers he was focusing on the following fields of study:
Combinatorics, Discrete mathematics, Upper and lower bounds, Algorithm and Bipartite graph are his primary areas of study.
His work on Vertex, Approximation algorithm and Binary logarithm is typically connected to Omega as part of general Combinatorics study, connecting several disciplines of science.
The study incorporates disciplines such as Graph, Model of computation, Computation and Streaming algorithm in addition to Discrete mathematics.
His Upper and lower bounds study combines topics from a wide range of disciplines, such as Conductance, Logarithm, Singular value decomposition, Function and Existential quantification.
His work in the fields of Algorithm, such as Property testing, intersects with other areas such as Running time.
His work deals with themes such as Private information retrieval and Partition, which intersect with Bipartite graph.
Between 2014 and 2021, his most popular works were:
- Maximum matchings in dynamic graph streams and the simultaneous communication model (65 citations)
- On estimating maximum matching size in graph streams (54 citations)
- Randomized Composable Coresets for Matching and Vertex Cover (39 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Computer network
- Programming language
Sanjeev Khanna mainly focuses on Discrete mathematics, Combinatorics, Upper and lower bounds, Streaming algorithm and Algorithm.
His studies in Discrete mathematics integrate themes in fields like Matching, Graph, Approximation algorithm and Computation.
His research in Approximation algorithm intersects with topics in Regular expression, Combinatory logic, Memory footprint and Programming paradigm.
His works in Open problem, Vertex, Vertex cover, Bipartite graph and Time complexity are all subjects of inquiry into Combinatorics.
His Streaming algorithm research incorporates elements of Java, Model of computation and Theoretical computer science, Communication complexity.
His work on Randomized algorithm as part of general Algorithm research is frequently linked to Running time, thereby connecting diverse disciplines of science.
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.
