What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Machine learning
- Statistics
Leszek Rutkowski mainly focuses on Artificial intelligence, Data mining, Soft computing, Data stream mining and Decision tree.
His Artificial intelligence study frequently links to other fields, such as Machine learning.
His work carried out in the field of Data mining brings together such families of science as Signature and Biometrics.
His Soft computing research incorporates themes from Cellular neural network and Artificial Intelligence System.
His research integrates issues of Data stream and Decision tree learning in his study of Data stream mining.
His Data stream study which covers Incremental decision tree that intersects with Task.
His most cited work include:
- Artificial Intelligence and Soft Computing (358 citations)
- Artificial Intelligence and Soft Computing – ICAISC 2006 (256 citations)
- Flexible neuro-fuzzy systems (232 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Artificial intelligence, Neuro-fuzzy, Artificial neural network, Machine learning and Fuzzy logic.
His study in Artificial intelligence is interdisciplinary in nature, drawing from both Data mining and Pattern recognition.
His study on Decision tree learning is often connected to Stream data as part of broader study in Data mining.
His Neuro-fuzzy study incorporates themes from Defuzzification, Fuzzy classification, Adaptive neuro fuzzy inference system and Membership function.
His research in Fuzzy classification tackles topics such as Fuzzy set operations which are related to areas like Fuzzy number.
His Artificial neural network research integrates issues from Algorithm, Probabilistic logic, Data stream mining and Regression.
He most often published in these fields:
- Artificial intelligence (58.85%)
- Neuro-fuzzy (27.43%)
- Artificial neural network (26.55%)
What were the highlights of his more recent work (between 2016-2021)?
- Artificial neural network (26.55%)
- Data stream mining (15.93%)
- Artificial intelligence (58.85%)
In recent papers he was focusing on the following fields of study:
Artificial neural network, Data stream mining, Artificial intelligence, Concept drift and Data mining are his primary areas of study.
His studies deal with areas such as Image, Applied mathematics and Control theory as well as Artificial neural network.
His study explores the link between Data stream mining and topics such as Regression that cross with problems in Regression analysis.
His work deals with themes such as Machine learning, Computer vision and Pattern recognition, which intersect with Artificial intelligence.
The various areas that Leszek Rutkowski examines in his Concept drift study include Algorithm and Estimator.
His study in the field of Decision tree also crosses realms of Stream data.
Between 2016 and 2021, his most popular works were:
- New Splitting Criteria for Decision Trees in Stationary Data Streams (53 citations)
- How to adjust an ensemble size in stream data mining (50 citations)
- Sliding-Mode Control for Slow-Sampling Singularly Perturbed Systems Subject to Markov Jump Parameters (46 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Machine learning
- Statistics
Leszek Rutkowski spends much of his time researching Artificial neural network, Data stream mining, Data stream, Control theory and Data mining.
His Artificial neural network study is concerned with Machine learning in general.
His Data stream mining study combines topics from a wide range of disciplines, such as Algorithm and Artificial intelligence.
His Artificial intelligence study integrates concerns from other disciplines, such as Function and Regression.
Leszek Rutkowski combines subjects such as Ensemble learning and Decision tree with his study of Data stream.
His Data mining research is multidisciplinary, incorporating perspectives in Fuzzy control system, Parameterized complexity, Structure, Interpretability and Discretization.
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