World's Best Scientists 2026 revealed!
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Computer Science
Germany
2025

D-Index & Metrics

Computer Science

D-Index
68
Citations
18030
World Ranking
2094
National Ranking
83

Research.com Recognitions

  • 2025 - Research.com Computer Science in Germany Leader Award
  • 2023 - Research.com Computer Science in Germany Leader Award
  • 2022 - Research.com Computer Science in Germany Leader Award

Overview

Helge Ritter is affiliated with Bielefeld University in Germany, with a research focus spanning multiple disciplines related to robotics, neuroscience, and engineering. Their body of work integrates insights from computer science, control systems, and cognitive neuroscience, reflecting a multidisciplinary approach.

The primary fields of study include:

  • Computer Science
  • Engineering
  • Neuroscience

This broad expertise is further detailed in subfields such as:

  • Cognitive Neuroscience
  • Artificial Intelligence
  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

The main research topics focus on applications and theory in robotics and neural systems, including:

  • Robot Manipulation and Learning
  • Tactile and Sensory Interactions
  • Teleoperation and Haptic Systems
  • Motor Control and Adaptation
  • EEG and Brain-Computer Interfaces
  • Reinforcement Learning in Robotics
  • Soft Robotics and Applications

Helge Ritter's publication record is extensive, with frequent contributions to the following venues:

  • arXiv (Cornell University)
  • IEEE Transactions on Robotics
  • IEEE Robotics and Automation Letters
  • PLoS ONE
  • Frontiers in Human Neuroscience

Among recent papers authored by or involving Helge Ritter, notable examples include:

  • A Review of Tactile Information: Perception and Action Through Touch (2020), IEEE Transactions on Robotics
  • Face Generation and Editing With StyleGAN: A Survey (2024), IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Object-Level Impedance Control for Dexterous In-Hand Manipulation (2020), IEEE Robotics and Automation Letters
  • Decentralized Control and Local Information for Robust and Adaptive Decentralized Deep Reinforcement Learning (2021), Neural Networks
  • Learning Optimal Impedance Control During Complex 3D Arm Movements (2021), IEEE Robotics and Automation Letters

Collaboration has been a consistent feature of their career. Frequent coauthors include:

  • Andrew Melnik
  • Robert Haschke
  • Luca Lach
  • Malte Schilling
  • Alexandra Moringen

Best Publications

  • Neural computation and self-organizing maps : an introduction

    Helge Ritter;Thomas Martinetz;Klaus Schulten;Daniel Barsky

  • Self-organizing semantic maps

    H. Ritter;T. Kohonen

  • BCI competition 2003-data set IIb: support vector machines for the P300 speller paradigm

    M. Kaper;P. Meinicke;U. Grossekathoefer;T. Lingner

  • Neural computation and self-organizing maps - an introduction

    Unknown

  • Topology-conserving maps for learning visuo-motor-coordination

    H. J. Ritter;T. M. Martinetz;K. J. Schulten

  • Convergence properties of Kohonen's topology conserving maps: fluctuations, stability, and dimension selection

    H. Ritter;K. Schulten

  • On the stationary state of Kohonen's self-organizing sensory mapping

    H Ritter;K Schulten

  • Three-dimensional neural net for learning visuomotor coordination of a robot arm

    T.M. Martinetz;H.J. Ritter;K.J. Schulten

  • A principle for the formation of the spatial structure of cortical feature maps.

    Klaus Obermayer;Helge Ritter;Klaus Schulten

  • A Review of Tactile Information: Perception and Action Through Touch

    Qiang Li;Oliver Kroemer;Zhe Su;Filipe Fernandes Veiga

  • Flexible and stretchable fabric-based tactile sensor

    Gereon H. Büscher;Risto Kõiva;Carsten Schürmann;Robert Haschke

  • An Adaptive P300-Based Online Brain–Computer Interface

    A. Lenhardt;M. Kaper;H.J. Ritter

  • Adaptive color segmentation-a comparison of neural and statistical methods

    E. Littmann;H. Ritter

  • Listen to your Data: Model-Based Sonification for Data Analysis

    Thomas Hermann;Helge Ritter

  • Self-Organizing Maps on non-euclidean Spaces

    Helge Ritter

  • 2009 Special Issue: The MindGame: A P300-based brain-computer interface game

    Andrea Finke;Alexander Lenhardt;Helge Ritter

  • On-line planning of time-optimal, jerk-limited trajectories

    R. Haschke;E. Weitnauer;H. Ritter

  • Recognition of human head orientation based on artificial neural networks

    R. Rae;H.J. Ritter

  • Platform portable anthropomorphic grasping with the bielefeld 20-DOF shadow and 9-DOF TUM hand

    F. Rothling;R. Haschke;J.J. Steil;H. Ritter

  • Visual recognition of continuous hand postures

    C. Nolker;H. Ritter

  • Disambiguating Complex Visual Information: Towards Communication of Personal Views of a Scene:

    Marc Pomplun;Helge Ritter;Boris Velichkovsky

  • Asymptotic level density for a class of vector quantization processes

    H. Ritter

Frequent Co-Authors

Jochen J. Steil
Jochen J. Steil Technische Universität Braunschweig
Gerhard Sagerer
Gerhard Sagerer Bielefeld University
Tim Wilhelm Nattkemper
Tim Wilhelm Nattkemper Bielefeld University
Marc Pomplun
Marc Pomplun University of Massachusetts Boston
Thomas Schack
Thomas Schack Bielefeld University
Klaus Obermayer
Klaus Obermayer Technical University of Berlin
Holk Cruse
Holk Cruse Bielefeld University
Gernot A. Fink
Gernot A. Fink TU Dortmund University
Yaochu Jin
Yaochu Jin Westlake University
Thomas Martinetz
Thomas Martinetz University of Lübeck

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