What is he best known for?
The fields of study he is best known for:
- Algorithm
- Artificial intelligence
- Computer network
Wireless sensor network, Key distribution in wireless sensor networks, Mathematical optimization, Algorithm and Point are his primary areas of study.
His Wireless sensor network research incorporates elements of Real-time computing and Boundary, Topology.
Sándor P. Fekete interconnects Tree traversal and Computational geometry in the investigation of issues within Mathematical optimization.
The various areas that Sándor P. Fekete examines in his Algorithm study include Wang tile and Constant.
As a member of one scientific family, Sándor P. Fekete mostly works in the field of Packing problems, focusing on Branch and bound and, on occasion, Scheduling and Discrete mathematics.
Within one scientific family, Sándor P. Fekete focuses on topics pertaining to Facility location problem under Approximation algorithm, and may sometimes address concerns connected to Combinatorics.
His most cited work include:
- Approximation algorithms for lawn mowing and milling (193 citations)
- Neighborhood-Based Topology Recognition in Sensor Networks (176 citations)
- Deterministic boundary recognition and topology extraction for large sensor networks (165 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Combinatorics, Wireless sensor network, Discrete mathematics, Distributed computing and Algorithm.
His Combinatorics research includes themes of Point and Set.
His Wireless sensor network study combines topics in areas such as Wireless, Key distribution in wireless sensor networks, Mobile wireless sensor network, Real-time computing and Topology.
His research investigates the link between Real-time computing and topics such as Embedded system that cross with problems in Scheduling.
His work carried out in the field of Algorithm brings together such families of science as Robot, Sequence, Swarm behaviour and Wang tile.
His research on Approximation algorithm concerns the broader Mathematical optimization.
He most often published in these fields:
- Combinatorics (23.67%)
- Wireless sensor network (14.98%)
- Discrete mathematics (14.01%)
What were the highlights of his more recent work (between 2015-2021)?
- Robot (10.63%)
- Combinatorics (23.67%)
- Scheduling (8.21%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Robot, Combinatorics, Scheduling, Algorithm and Set.
His study in Robot is interdisciplinary in nature, drawing from both Distributed algorithm, Path, Swarm behaviour and Computer vision.
His research integrates issues of Point, Plane and Regular polygon in his study of Combinatorics.
His Scheduling study combines topics from a wide range of disciplines, such as Field-programmable gate array, Control reconfiguration and Satellite.
His studies in Algorithm integrate themes in fields like Workspace and Sequence.
His Set research is multidisciplinary, incorporating perspectives in Incircle and excircles of a triangle and Circle packing, Tetrahedron packing, Packing problems.
Between 2015 and 2021, his most popular works were:
- Particle computation: complexity, algorithms, and logic (15 citations)
- Structured triangulation in multi-robot systems (15 citations)
- Three colors suffice: conflict-free coloring of planar graphs (10 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Artificial intelligence
- Computer network
Sándor P. Fekete mainly investigates Algorithm, Workspace, Combinatorics, Discrete mathematics and Computation.
His research in Algorithm intersects with topics in Set and Task.
He has researched Set in several fields, including Function, Sequence and Polyomino.
He incorporates Combinatorics and Conflict free in his research.
Particularly relevant to Brooks' theorem is his body of work in Discrete mathematics.
His biological study spans a wide range of topics, including Universal logic, Logic gate, Software and Theory of computation.
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.
