What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Algorithm
Ulrik Brandes spends much of his time researching Theoretical computer science, Graph drawing, Centrality, Network theory and Betweenness centrality.
His Theoretical computer science research incorporates elements of Machine learning, Graph, Computation and Graph.
His Graph drawing study incorporates themes from Social network analysis, Data visualization and Electronic data interchange.
Betweenness centrality is a component of his Katz centrality and Random walk closeness centrality studies.
Ulrik Brandes interconnects Alpha centrality and Network controllability in the investigation of issues within Katz centrality.
His biological study spans a wide range of topics, including Binary logarithm, Measure, Girvan–Newman algorithm and Range.
His most cited work include:
- A faster algorithm for betweenness centrality (2987 citations)
- On Modularity Clustering (856 citations)
- On variants of shortest-path betweenness centrality and their generic computation ☆ (560 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Theoretical computer science, Graph drawing, Combinatorics, Graph and Graph.
The Theoretical computer science study combines topics in areas such as Betweenness centrality, Centrality, Graph Layout and Algorithm, Computation.
His Betweenness centrality research focuses on Katz centrality and Random walk closeness centrality.
The Graph drawing study which covers Force-directed graph drawing that intersects with Lattice graph.
His work focuses on many connections between Combinatorics and other disciplines, such as Discrete mathematics, that overlap with his field of interest in Tree.
His research investigates the link between Graph and topics such as Cluster analysis that cross with problems in Graph partition.
He most often published in these fields:
- Theoretical computer science (22.78%)
- Graph drawing (20.68%)
- Combinatorics (16.88%)
What were the highlights of his more recent work (between 2014-2020)?
- Centrality (9.28%)
- Algorithm (12.24%)
- Network science (5.49%)
In recent papers he was focusing on the following fields of study:
His main research concerns Centrality, Algorithm, Network science, Theoretical computer science and Graph.
His Centrality research incorporates themes from Discrete mathematics and Network theory.
His biological study deals with issues like Duality, which deal with fields such as Combinatorics.
His Algorithm study combines topics from a wide range of disciplines, such as Space, Embedding, Preprocessor and Aggregate.
His Theoretical computer science research is multidisciplinary, relying on both Sampling, Network model, Computation and Subroutine.
He has researched Graph in several fields, including Model of computation and Graph.
Between 2014 and 2020, his most popular works were:
- Maintaining the duality of closeness and betweenness centrality (84 citations)
- Investigating human geographic origins using dual-isotope (87Sr/86Sr, δ18O) assignment approaches. (47 citations)
- Quality Metrics for Information Visualization (45 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Algorithm
The scientist’s investigation covers issues in Centrality, Katz centrality, Betweenness centrality, Network theory and Random walk closeness centrality.
His Katz centrality research includes elements of Axiom, Conceptual framework and Correlation.
To a larger extent, Ulrik Brandes studies Combinatorics with the aim of understanding Betweenness centrality.
His work carried out in the field of Random walk closeness centrality brings together such families of science as Star, Property, Generalization and Pairwise comparison.
His study looks at the intersection of Network controllability and topics like Topology with Theoretical computer science.
His Theoretical computer science study integrates concerns from other disciplines, such as Basis, Social network analysis and Graph drawing, Graph embedding, Graph.
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