H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 60 Citations 18,170 278 World Ranking 1545 National Ranking 861

Research.com Recognitions

Awards & Achievements

2020 - Evolutionary Computation Pioneer Award, IEEE Computational Intelligence Society

2016 - IEEE Fellow For contributions to neural and evolutionary computation

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Artificial neural network
  • Machine learning

Risto Miikkulainen mostly deals with Artificial intelligence, Artificial neural network, Neuroevolution, Neuroevolution of augmenting topologies and Machine learning. His Artificial intelligence research focuses on subjects like Natural language processing, which are linked to Lexical semantics. His Artificial neural network research focuses on Evolutionary acquisition of neural topologies in particular.

His studies in Neuroevolution integrate themes in fields like Control theory, Inverted pendulum, Multi-agent system, Combinatorial game theory and Game art design. As a part of the same scientific family, he mostly works in the field of Neuroevolution of augmenting topologies, focusing on HyperNEAT and, on occasion, Artificial development, CMA-ES and General video game playing. His Machine learning research is multidisciplinary, incorporating elements of Data mining and Set.

His most cited work include:

  • Evolving neural networks through augmenting topologies (2279 citations)
  • Evolving Deep Neural Networks (464 citations)
  • Intrusion Detection with Neural Networks (397 citations)

What are the main themes of his work throughout his whole career to date?

His primary scientific interests are in Artificial intelligence, Artificial neural network, Machine learning, Neuroevolution and Evolutionary computation. Risto Miikkulainen usually deals with Artificial intelligence and limits it to topics linked to Computer vision and Visual cortex. His study in Visual cortex is interdisciplinary in nature, drawing from both Orientation, Receptive field and Hebbian theory.

His work carried out in the field of Artificial neural network brings together such families of science as Robot, Coevolution and Metalearning. Risto Miikkulainen interconnects Contextual image classification and Novelty in the investigation of issues within Machine learning. His Neuroevolution research is multidisciplinary, incorporating perspectives in Intelligent agent, Task and Set.

He most often published in these fields:

  • Artificial intelligence (68.27%)
  • Artificial neural network (40.14%)
  • Machine learning (26.20%)

What were the highlights of his more recent work (between 2017-2021)?

  • Artificial intelligence (68.27%)
  • Machine learning (26.20%)
  • Artificial neural network (40.14%)

In recent papers he was focusing on the following fields of study:

Risto Miikkulainen mainly investigates Artificial intelligence, Machine learning, Artificial neural network, Deep learning and Evolutionary computation. His research links Multi-task learning with Artificial intelligence. In his research on the topic of Machine learning, Selection is strongly related with Novelty.

In the subject of general Artificial neural network, his work in Gradient descent is often linked to Gaussian process, thereby combining diverse domains of study. His Deep learning research also works with subjects such as

  • Set most often made with reference to Benchmark,
  • Activation function that connect with fields like Crossover. The various areas that he examines in his Evolutionary computation study include Creativity and Artificial life.

Between 2017 and 2021, his most popular works were:

  • Designing neural networks through neuroevolution (201 citations)
  • Evolutionary architecture search for deep multitask networks (69 citations)
  • The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities (69 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Artificial neural network

His primary areas of investigation include Artificial intelligence, Machine learning, Artificial neural network, Deep learning and Hyperparameter. His research integrates issues of Multi-task learning and State in his study of Artificial intelligence. His Selection study, which is part of a larger body of work in Machine learning, is frequently linked to Regression, bridging the gap between disciplines.

Particularly relevant to Recurrent neural network is his body of work in Artificial neural network. In his research, Backpropagation, Neuroevolution and Stochastic gradient descent is intimately related to Evolutionary algorithm, which falls under the overarching field of Deep learning. He combines subjects such as Contextual image classification and Genetic programming with his study of Hyperparameter.

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.

Top Publications

Evolving neural networks through augmenting topologies

Kenneth O. Stanley;Risto Miikkulainen.
Evolutionary Computation (2002)

3322 Citations

Intrusion Detection with Neural Networks

Jake Ryan;Meng-Jang Lin;Risto Miikkulainen.
neural information processing systems (1997)

753 Citations

Evolving Deep Neural Networks

Risto Miikkulainen;Jason Zhi Liang;Elliot Meyerson;Aditya Rawal.
arXiv: Neural and Evolutionary Computing (2017)

710 Citations

A Taxonomy for artificial embryogeny

Kenneth O. Stanley;Risto Miikkulainen.
Artificial Life (2003)

567 Citations

Competitive coevolution through evolutionary complexification

Kenneth O. Stanley;Risto Miikkulainen.
Journal of Artificial Intelligence Research (2004)

521 Citations

Real-time neuroevolution in the NERO video game

K.O. Stanley;B.D. Bryant;R. Miikkulainen.
IEEE Transactions on Evolutionary Computation (2005)

481 Citations

Subsymbolic Natural Language Processing: An Integrated Model of Scripts, Lexicon, and Memory

Risto Miikkulainen.
(1993)

457 Citations

Forming neural networks through efficient and adaptive coevolution

David E. Moriarty;Risto Miikkulainen.
Evolutionary Computation (1997)

425 Citations

Computational Maps in the Visual Cortex

Risto Miikkulainen;James A. Bednar;Yoonsuck Choe;Joseph Sirosh.
(2005)

367 Citations

Efficient Reinforcement Learning Through Evolving Neural Network Topologies

Kenneth O. Stanley;Risto Miikkulainen.
genetic and evolutionary computation conference (2002)

351 Citations

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.

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