What is he best known for?
The fields of study he is best known for:
- Algorithm
- Artificial intelligence
- Operating system
Peter Widmayer mainly investigates Combinatorics, Theoretical computer science, Mobile robot, Distributed computing and Range query.
His Combinatorics research is multidisciplinary, relying on both Discrete mathematics and Theory of computation.
His study looks at the intersection of Theoretical computer science and topics like Search tree with Tree structure.
The concepts of his Distributed computing study are interwoven with issues in Computability, Robotics and Complete graph.
His Range query study integrates concerns from other disciplines, such as Structure, Gray code, Spatial analysis and Data structure.
His Data mining study combines topics from a wide range of disciplines, such as Expression, Software development and Database.
His most cited work include:
- Genevestigator v3: a reference expression database for the meta-analysis of transcriptomes. (1475 citations)
- An asymptotically optimal multiversion B-tree (357 citations)
- Gathering of asynchronous robots with limited visibility (332 citations)
What are the main themes of his work throughout his whole career to date?
Peter Widmayer mostly deals with Combinatorics, Theoretical computer science, Algorithm, Discrete mathematics and Time complexity.
His Combinatorics course of study focuses on Set and Simple.
His research in Theoretical computer science intersects with topics in Robot, Spatial analysis and Data structure.
His research integrates issues of Range query and Message passing in his study of Data structure.
His biological study spans a wide range of topics, including Upper and lower bounds and Mathematical optimization.
His Mathematical optimization research is multidisciplinary, incorporating perspectives in Competitive analysis and Robustness.
He most often published in these fields:
- Combinatorics (28.27%)
- Theoretical computer science (14.35%)
- Algorithm (14.35%)
What were the highlights of his more recent work (between 2011-2018)?
- Combinatorics (28.27%)
- Discrete mathematics (13.08%)
- Algorithm (14.35%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Combinatorics, Discrete mathematics, Algorithm, Graph and Mathematical optimization.
Peter Widmayer interconnects Polygon covering and Simple polygon in the investigation of issues within Combinatorics.
His study in Simple polygon is interdisciplinary in nature, drawing from both Exact geometry and Mobile robot.
His studies deal with areas such as Theory of computation and Maximization as well as Discrete mathematics.
His Algorithm research incorporates elements of Theoretical computer science, Heuristics and Query optimization.
His work deals with themes such as Energy constrained, Energy and Probability distribution, which intersect with Mathematical optimization.
Between 2011 and 2018, his most popular works were:
- Mathematical Foundations of Computer Science 2012 (38 citations)
- Data Delivery by Energy-Constrained Mobile Agents (27 citations)
- Data Delivery by Energy-Constrained Mobile Agents on a Line (21 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Artificial intelligence
- Operating system
His primary scientific interests are in Combinatorics, Mathematical optimization, Visibility graph, Discrete mathematics and Visibility polygon.
His Combinatorics study combines topics in areas such as Graph center, Path graph and Wheel graph.
His Mathematical optimization research includes elements of Data delivery, Probability distribution and Energy constrained, Energy.
His Energy research incorporates themes from Point and Schedule.
He has researched Discrete mathematics in several fields, including Scheme, Approximation algorithm, Directed acyclic graph, Theory of computation and Floyd–Warshall algorithm.
The various areas that Peter Widmayer examines in his Visibility polygon study include Point in polygon, Robot and Equiangular polygon.
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.
