What is he best known for?
The fields of study he is best known for:
- Algorithm
- Mathematical optimization
- Artificial intelligence
Thomas Jansen mostly deals with Evolutionary algorithm, Mathematical optimization, Evolutionary computation, Heuristics and Algorithm.
His Evolutionary algorithm study incorporates themes from Genetic algorithm, Polynomial and Crossover.
His work carried out in the field of Polynomial brings together such families of science as Unimodality, Randomized search, Mutation rate and Degree.
His Evolutionary computation research is multidisciplinary, incorporating perspectives in Memetic algorithm, Management science and Cultural algorithm.
His Heuristics study combines topics from a wide range of disciplines, such as Beam search and Search algorithm.
His work in Algorithm addresses issues such as Exponential function, which are connected to fields such as Simple.
His most cited work include:
- On the analysis of the (1+ 1) evolutionary algorithm (752 citations)
- Upper and Lower Bounds for Randomized Search Heuristics in Black-Box Optimization (213 citations)
- Parallel Problem Solving from Nature – PPSN X (203 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Evolutionary algorithm, Mathematical optimization, Heuristics, Evolutionary computation and Algorithm.
His work deals with themes such as Function, Genetic algorithm and Theoretical computer science, which intersect with Evolutionary algorithm.
His work on Search algorithm, Optimization problem and Simulated annealing is typically connected to Point as part of general Mathematical optimization study, connecting several disciplines of science.
The concepts of his Heuristics study are interwoven with issues in Local search, Artificial immune system and Heuristic.
His Algorithm study integrates concerns from other disciplines, such as Crossover, Exponential function, Polynomial and Mutation.
His studies deal with areas such as Memetic algorithm and Cultural algorithm as well as Evolutionary programming.
He most often published in these fields:
- Evolutionary algorithm (74.31%)
- Mathematical optimization (42.20%)
- Heuristics (36.70%)
What were the highlights of his more recent work (between 2014-2020)?
- Mathematical optimization (42.20%)
- Heuristics (36.70%)
- Evolutionary algorithm (74.31%)
In recent papers he was focusing on the following fields of study:
His main research concerns Mathematical optimization, Heuristics, Evolutionary algorithm, Artificial intelligence and Simple.
The various areas that Thomas Jansen examines in his Mathematical optimization study include Range, Selection and FP.
His Heuristics research focuses on Perspective and how it relates to Computational intelligence and Evolutionary computation.
His research on Evolutionary algorithm also deals with topics like
- Artificial immune system together with Algorithm and Preprocessor,
- Tracking together with Population based algorithm and Natural class.
He combines subjects such as Function, Exponential function and Mutation with his study of Algorithm.
His work on Crossover as part of general Artificial intelligence study is frequently linked to ROWE, bridging the gap between disciplines.
Between 2014 and 2020, his most popular works were:
- Analyzing Evolutionary Algorithms (94 citations)
- Populations Can Be Essential in Tracking Dynamic Optima (22 citations)
- On Easiest Functions for Mutation Operators in Bio-Inspired Optimisation (14 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Artificial intelligence
- Mathematical optimization
His primary areas of study are Mathematical optimization, Evolutionary algorithm, Heuristics, Theory of computation and Artificial intelligence.
His Mathematical optimization research incorporates themes from Time complexity, Worst-case complexity, Descriptive complexity theory, Complexity index and Structural complexity theory.
Thomas Jansen applies his multidisciplinary studies on Evolutionary algorithm and Upper and lower bounds in his research.
His Heuristics research integrates issues from Evolutionary computation, Perspective and Computational intelligence.
His Theory of computation study combines topics in areas such as Tracking, Population based algorithm, Function, Large population and Natural class.
His Artificial intelligence research is multidisciplinary, relying on both Simple, Fitness landscape and Machine learning.
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.
