What is he best known for?
The fields of study he is best known for:
- Computer network
- Algorithm
- Programming language
David Peleg mainly focuses on Combinatorics, Discrete mathematics, Distributed algorithm, Distributed computing and Binary logarithm.
His Combinatorics study often links to related topics such as Upper and lower bounds.
David Peleg frequently studies issues relating to Graph theory and Discrete mathematics.
The concepts of his Distributed algorithm study are interwoven with issues in Grid computing, Theoretical computer science, Distributed concurrency control and Unconventional computing.
In general Distributed computing study, his work on Distributed design patterns often relates to the realm of Fabric computing, thereby connecting several areas of interest.
His Binary logarithm research incorporates elements of Asymptotically optimal algorithm, Graph labeling, Broadcasting and Randomized algorithm.
His most cited work include:
- Distributed Computing: A Locality-Sensitive Approach (1196 citations)
- The Dense k -Subgraph Problem (496 citations)
- A lower bound for radio broadcast (354 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Combinatorics, Discrete mathematics, Upper and lower bounds, Theoretical computer science and Distributed computing.
Graph, Spanning tree, Binary logarithm, Vertex and Approximation algorithm are subfields of Combinatorics in which his conducts study.
His work is dedicated to discovering how Discrete mathematics, Algorithm are connected with Asynchronous communication and other disciplines.
His research in Theoretical computer science intersects with topics in Node and Set.
David Peleg is involved in the study of Distributed computing that focuses on Fault tolerance in particular.
His work deals with themes such as Distributed algorithm, Randomized algorithm and Graph, which intersect with Time complexity.
He most often published in these fields:
- Combinatorics (35.80%)
- Discrete mathematics (27.69%)
- Upper and lower bounds (13.76%)
What were the highlights of his more recent work (between 2014-2021)?
- Combinatorics (35.80%)
- Discrete mathematics (27.69%)
- Graph (11.11%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Combinatorics, Discrete mathematics, Graph, Obstetrics and Vertex.
His Combinatorics study frequently draws parallels with other fields, such as Upper and lower bounds.
His studies deal with areas such as Distributed algorithm, Radio networks, Time complexity and Matching as well as Upper and lower bounds.
Within one scientific family, David Peleg focuses on topics pertaining to Preferential attachment under Discrete mathematics, and may sometimes address concerns connected to Hypergraph and Homophily.
His Graph research is multidisciplinary, incorporating perspectives in Fault tolerance and Realizability.
The Obstetrics study which covers Pregnancy that intersects with Internal medicine.
Between 2014 and 2021, his most popular works were:
- On the Complexity of Universal Leader Election (46 citations)
- Dynamic (1 + ε)-approximate matchings: a density-sensitive approach (27 citations)
- Homophily and the Glass Ceiling Effect in Social Networks (27 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Programming language
- Algorithm
His primary areas of study are Combinatorics, Discrete mathematics, Graph, Theoretical computer science and Vertex.
His research is interdisciplinary, bridging the disciplines of Upper and lower bounds and Combinatorics.
The Upper and lower bounds study combines topics in areas such as Leader election, Matching, Distributed algorithm, Randomized algorithm and Spanning tree.
David Peleg focuses mostly in the field of Graph, narrowing it down to matters related to Fault tolerance and, in some cases, Spanner, Graph algorithms and Multiplicative function.
His research integrates issues of Graph, Tree, Node, Robot and Computation in his study of Theoretical computer science.
The various areas that David Peleg examines in his Vertex study include Edge-graceful labeling, Realizability, Bounded function and Distance labeling.
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