World's Best Scientists 2026 revealed!
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Electronics and Electrical Engineering
USA
2026

D-Index & Metrics

Computer Science

D-Index
102
Citations
46429
World Ranking
336
National Ranking
183

Electronics and Electrical Engineering

D-Index
99
Citations
42544
World Ranking
190
National Ranking
93

Research.com Recognitions

  • 2026 - Research.com Electronics and Electrical Engineering in United States Leader Award
  • 2025 - Research.com Electronics and Electrical Engineering in United States Leader Award
  • 2014 - IEEE Fellow For contributions to robot learning and modular motion planning

Overview

Stefan Schaal is affiliated with Google in the United States and works primarily in the fields of Computer Science, Engineering, and Neuroscience. Their research integrates subfields such as Cognitive Neuroscience, Control and Systems Engineering, and Artificial Intelligence.

Their work spans several main topics, notably:

  • Robot Manipulation and Learning
  • Motor Control and Adaptation
  • EEG and Brain-Computer Interfaces
  • Neural and Behavioral Psychology Studies
  • Reinforcement Learning in Robotics
  • Machine Learning and Algorithms
  • Robotics and Sensor-Based Localization

Recent publications by Stefan Schaal include the following:

  • Action planning and control under uncertainty emerge through a desirability-driven competition between parallel encoding motor plans, 2021, PLoS Computational Biology
  • Detection and Physical Interaction with Deformable Linear Objects, 2022, arXiv (Cornell University)
  • Scaling Simulation-to-Real Transfer by Learning Composable Robot Skills, 2020, Springer proceedings in advanced robotics
  • An Interior Point Method Solving Motion Planning Problems with Narrow Passages, 2020, arXiv (Cornell University)

The frequent coauthors collaborating with Schaal include:

  • Vince Enachescu
  • Paul Schrater
  • Vassilios Christopoulos
  • Ryan Julian
  • Eric Heiden

Stefan Schaal's research has been disseminated in several publication venues, primarily:

  • arXiv (Cornell University)
  • PLoS Computational Biology
  • Springer proceedings in advanced robotics

The scientist has received recognition in the form of the IEEE Fellow award in 2014 for contributions to robot learning and modular motion planning.

Best Publications

  • Locally Weighted Learning

    Christopher G. Atkeson;Andrew W. Moore;Stefan Schaal

  • Is imitation learning the route to humanoid robots

    Stefan Schaal

  • Dynamical movement primitives: Learning attractor models for motor behaviors

    Auke Jan Ijspeert;Jun Nakanishi;Heiko Hoffmann;Peter Pastor

  • 2008 Special Issue: Reinforcement learning of motor skills with policy gradients

    Jan Peters;Stefan Schaal

  • Natural actor-critic

    Jan Peters;Sethu Vijayakumar;Stefan Schaal

  • Natural Actor-Critic

    Jan Peters;Stefan Schaal

  • Movement imitation with nonlinear dynamical systems in humanoid robots

    A.J. Ijspeert;J. Nakanishi;S. Schaal

  • STOMP: Stochastic trajectory optimization for motion planning

    Mrinal Kalakrishnan;Sachin Chitta;Evangelos Theodorou;Peter Pastor

  • Robot Programming by Demonstration

    Unknown

  • Learning and generalization of motor skills by learning from demonstration

    Peter Pastor;Heiko Hoffmann;Tamim Asfour;Stefan Schaal

  • Locally weighted learning for control

    Christopher G. Atkeson;Andrew W. Moore;Stefan Schaal

  • Learning Attractor Landscapes for Learning Motor Primitives

    Auke J. Ijspeert;Jun Nakanishi;Stefan Schaal

  • Computational approaches to motor learning by imitation

    Stefan Schaal;Auke Ijspeert;Aude Billard;Aude Billard

  • Robot Learning From Demonstration

    Christopher G. Atkeson;Stefan Schaal

  • Constructive incremental learning from only local information

    Stefan Schaal;Christopher G. Atkeson

  • Dynamic Movement Primitives -A Framework for Motor Control in Humans and Humanoid Robotics

    Stefan Schaal

  • Policy Gradient Methods for Robotics

    J. Peters;S. Schaal

  • Incremental Online Learning in High Dimensions

    Sethu Vijayakumar;Aaron D'souza;Stefan Schaal

  • A Generalized Path Integral Control Approach to Reinforcement Learning

    Evangelos Theodorou;Jonas Buchli;Stefan Schaal

  • Learning from Demonstration

    Stefan Schaal

  • Time-Contrastive Networks: Self-Supervised Learning from Video

    Pierre Sermanet;Corey Lynch;Yevgen Chebotar;Jasmine Hsu

  • Erratum: A Generalized Path Integral Control Approach to Reinforcement Learning

    Evangelos A. Theodorou;Jonas Buchli;Stefan Schaal;Daniel Lee

Frequent Co-Authors

Ludovic Righetti
Ludovic Righetti New York University
Sethu Vijayakumar
Sethu Vijayakumar University of Edinburgh
Jan Peters
Jan Peters Technical University of Darmstadt
Jonas Buchli
Jonas Buchli DeepMind (United Kingdom)
Gaurav S. Sukhatme
Gaurav S. Sukhatme University of Southern California
Jeannette Bohg
Jeannette Bohg Stanford University
Evangelos A. Theodorou
Evangelos A. Theodorou Georgia Institute of Technology
Auke Jan Ijspeert
Auke Jan Ijspeert École Polytechnique Fédérale de Lausanne
Christopher G. Atkeson
Christopher G. Atkeson Carnegie Mellon University
Freek Stulp
Freek Stulp German Aerospace Center

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