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Computer Science

D-Index
54
Citations
11066
World Ranking
4594
National Ranking
205

Electronics and Electrical Engineering

D-Index
54
Citations
11702
World Ranking
2274
National Ranking
68

Research.com Recognitions

  • 2017 - IEEE Fellow For contributions in humanoid robotics systems and neurorobotics

Overview

Gordon Cheng is affiliated with the Technical University of Munich in Germany. Their research spans the intersecting fields of neuroscience and engineering, with a notable contribution to subfields such as cognitive neuroscience, biomedical engineering, cellular and molecular neuroscience, social psychology, and control and systems engineering.

The main topics explored in their work include EEG and brain-computer interfaces, muscle activation and electromyography studies, neural dynamics and brain function, neuroscience and neural engineering, prosthetics and rehabilitation robotics, advanced sensor and energy harvesting materials, and robot manipulation and learning.

Recent publications by Gordon Cheng include:

  • "Nanomesh pressure sensor for monitoring finger manipulation without sensory interference," 2020, Science
  • "Perception and Evaluation in Human-Robot Interaction: The Human-Robot Interaction Evaluation Scale (HRIES)-A Multicomponent Approach of Anthropomorphism," 2021, International Journal of Social Robotics
  • "Inertial Parameter Identification in Robotics: A Survey," 2021, Applied Sciences
  • "An Empirical Study of Active Inference on a Humanoid Robot," 2021, IEEE Transactions on Cognitive and Developmental Systems
  • "Neuroengineering challenges of fusing robotics and neuroscience," 2020, Science Robotics

Frequent co-authors collaborating with Cheng include:

  • J. Rogelio Guadarrama-Olvera
  • Stefan K. Ehrlich
  • Nitish V. Thakor
  • Nicolas Berberich
  • Emmanuel Dean-León

Their published work is commonly featured in venues such as IEEE Robotics and Automation Letters, Scientific Reports, Advanced Intelligent Systems, arXiv (Cornell University), and IEEE Transactions on Medical Robotics and Bionics.

Gordon Cheng has been recognized as an IEEE Fellow since 2017 for contributions in humanoid robotics systems and neurorobotics.

Best Publications

  • Nanomesh pressure sensor for monitoring finger manipulation without sensory interference

    Sunghoon Lee;Sae Franklin;Faezeh Arab Hassani;Tomoyuki Yokota

  • Learning from demonstration and adaptation of biped locomotion

    Jun Nakanishi;Jun Morimoto;Gen Endo;Gordon Cheng

  • Directions Toward Effective Utilization of Tactile Skin: A Review

    Ravinder S. Dahiya;Philipp Mittendorfer;Maurizio Valle;Gordon Cheng

  • Full-Body Compliant Human–Humanoid Interaction: Balancing in the Presence of Unknown External Forces

    Sang-Ho Hyon;J.G. Hale;G. Cheng

  • Humanoid Multimodal Tactile-Sensing Modules

    P Mittendorfer;G Cheng

  • CB: A Humanoid Research Platform for Exploring NeuroScience

    G. Cheng;Sang-Ho Hyon;J. Morimoto;A. Ude

  • Learning CPG-based Biped Locomotion with a Policy Gradient Method: Application to a Humanoid Robot

    Gen Endo;Jun Morimoto;Takamitsu Matsubara;Jun Nakanishi

  • Discovering optimal imitation strategies

    Aude Billard;Aude Billard;Yann Epars;Sylvain Calinon;Stefan Schaal

  • ROBOT APPARATUS AND A METHOD FOR CONTROLLING THE POSTURE OF A ROBOT FOR STABILIZING THE POSTURE OF THE ROBOT ACCORDING TO PERIODICAL MOTION

    Cheng Gordon;Endo Gen;Kawato Mitsuo;Morimoto Jun

  • Experimental Studies of a Neural Oscillator for Biped Locomotion with QRIO

    Gen Endo;Jun Nakanishi;Jun Morimoto;G. Cheng

  • New materials and advances in making electronic skin for interactive robots

    Nivasan Yogeswaran;Wenting Dang;William Navaraj;Dhayalan Shakthivel

  • A Comprehensive Realization of Robot Skin: Sensors, Sensing, Control, and Applications

    Gordon Cheng;Emmanuel Dean-Leon;Florian Bergner;Julio Rogelio Guadarrama Olvera

  • Validating Deep Neural Networks for Online Decoding of Motor Imagery Movements from EEG Signals

    Zied Tayeb;Juri Fedjaev;Nejla Ghaboosi;Christoph Richter

  • A Biologically Inspired Biped Locomotion Strategy for Humanoid Robots: Modulation of Sinusoidal Patterns by a Coupled Oscillator Model

    J. Morimoto;G. Endo;J. Nakanishi;G. Cheng

  • An empirical exploration of a neural oscillator for biped locomotion control

    G. Endo;J. Morimoto;J. Nakanishi;G. Cheng

  • Learning tasks from observation and practice

    Darrin C. Bentivegna;Christopher G. Atkeson;Gordon Cheng

  • Transferring skills to humanoid robots by extracting semantic representations from observations of human activities

    Karinne Ramirez-Amaro;Michael Beetz;Gordon Cheng

  • A simple reinforcement learning algorithm for biped walking

    J. Morimoto;G. Cheng;C.G. Atkeson;G. Zeglin

  • A review on neural network models of schizophrenia and autism spectrum disorder

    Pablo Lanillos;Daniel Oliva;Anja Philippsen;Yuichi Yamashita

  • Realizing whole-body tactile interactions with a self-organizing, multi-modal artificial skin on a humanoid robot

    Philipp Mittendorfer;Eiichi Yoshida;Gordon Cheng

  • How do we think machines think? An fMRI study of alleged competition with an artificial intelligence

    Thierry Chaminade;Delphine Rosset;David Da Fonseca;Bruno Nazarian

  • Social cognitive neuroscience and humanoid robotics.

    Thierry Chaminade;Gordon Cheng

Frequent Co-Authors

Jun Morimoto
Jun Morimoto Advanced Telecommunications Research Institute International
Gen Endo
Gen Endo Tokyo Institute of Technology
Christopher G. Atkeson
Christopher G. Atkeson Carnegie Mellon University
Ales Ude
Ales Ude Jožef Stefan Institute
Michael Beetz
Michael Beetz University of Bremen
Yasuo Kuniyoshi
Yasuo Kuniyoshi University of Tokyo
Alexander Zelinsky
Alexander Zelinsky University of Newcastle Australia
Agnieszka Wykowska
Agnieszka Wykowska Italian Institute of Technology
Stefan Schaal
Stefan Schaal Google (United States)
Mitsuo Kawato
Mitsuo Kawato Advanced Telecommunications Research Institute International

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