World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
85
Citations
23532
World Ranking
398
National Ranking
16

Chenguang Yang publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Chenguang Yang sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 493 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Chenguang Yang D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Chenguang Yang sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 85 D-Index — 95th percentile

95% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Overview

Chenguang Yang is affiliated with the University of Liverpool in the United Kingdom. Their research spans across the fields of Engineering and Computer Science, with a specific focus on Control and Systems Engineering, Biomedical Engineering, Artificial Intelligence, Mechanical Engineering, and Computer Vision and Pattern Recognition.

Their work extensively covers topics including Robot Manipulation and Learning, Soft Robotics and Applications, Teleoperation and Haptic Systems, Adaptive Control of Nonlinear Systems, Muscle Activation and Electromyography Studies, Iterative Learning Control Systems, and Adaptive Dynamic Programming Control.

Frequent collaborators include Ning Wang, Zhenyu Lu, Weiyong Si, Yiming Jiang, and Chao Zeng. Yang's publications often appear in prominent venues such as IEEE Transactions on Automation Science and Engineering, IEEE Transactions on Industrial Electronics, IEEE/ASME Transactions on Mechatronics, arXiv (Cornell University), and IEEE Transactions on Systems Man and Cybernetics Systems.

Recent papers authored or co-authored by Yang include the following:

  • Neural Control of Robot Manipulators With Trajectory Tracking Constraints and Input Saturation, 2020, IEEE Transactions on Neural Networks and Learning Systems
  • Admittance-Based Controller Design for Physical Human-Robot Interaction in the Constrained Task Space, 2020, IEEE Transactions on Automation Science and Engineering
  • Reinforcement Learning Control of a Flexible Two-Link Manipulator: An Experimental Investigation, 2020, IEEE Transactions on Systems Man and Cybernetics Systems
  • 2022 IEEE International Conference on Robotics and Biomimetics, 2022, 2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)
  • Adaptive Leader-Follower Formation Control of Underactuated Surface Vehicles With Guaranteed Performance, 2020, IEEE Transactions on Systems Man and Cybernetics Systems

Chenguang Yang has authored academic books published by Springer Nature, including "Advanced Teleoperation and Robot Learning for Dexterous Manipulation," expected in 2025.

Best Publications

  • Extended State Observer-Based Integral Sliding Mode Control for an Underwater Robot With Unknown Disturbances and Uncertain Nonlinearities

    Unknown

  • Adaptive Neural Network Control of AUVs With Control Input Nonlinearities Using Reinforcement Learning

    Rongxin Cui;Chenguang Yang;Yang Li;Sanjay Sharma

  • Adaptive Parameter Estimation and Control Design for Robot Manipulators With Finite-Time Convergence

    Chenguang Yang;Yiming Jiang;Wei He;Jing Na

  • Human-Like Adaptation of Force and Impedance in Stable and Unstable Interactions

    Chenguang Yang;G. Ganesh;S. Haddadin;S. Parusel

  • Neural Control of Bimanual Robots With Guaranteed Global Stability and Motion Precision

    Chenguang Yang;Yiming Jiang;Zhijun Li;Wei He

  • Neural network-based motion control of an underactuated wheeled inverted pendulum model.

    Chenguang Yang;Zhijun Li;Rongxin Cui;Bugong Xu

  • Composite Neural Dynamic Surface Control of a Class of Uncertain Nonlinear Systems in Strict-Feedback Form

    Bin Xu;Zhongke Shi;Chenguang Yang;Fuchun Sun

  • Investigating aluminum alloy reinforced by graphene nanoflakes

    S.J. Yan;S.L. Dai;X.Y. Zhang;C. Yang

  • Global Neural Dynamic Surface Tracking Control of Strict-Feedback Systems With Application to Hypersonic Flight Vehicle

    Bin Xu;Chenguang Yang;Yongping Pan

  • Teleoperation Control Based on Combination of Wave Variable and Neural Networks

    Chenguang Yang;Xingjian Wang;Zhijun Li;Yanan Li

  • Robot Learning System Based on Adaptive Neural Control and Dynamic Movement Primitives

    Chenguang Yang;Chuize Chen;Wei He;Rongxin Cui

  • Corrections to “Extended State Observer-Based Integral Sliding Mode Control for an Underwater Robot With Unknown Disturbances and Uncertain Nonlinearities”

    Rongxin Cui;Lepeng Chen;Chenguang Yang;Mou Chen

  • Neural-Learning-Based Telerobot Control With Guaranteed Performance

    Chenguang Yang;Xinyu Wang;Long Cheng;Hongbin Ma

  • Finite-Time Convergence Adaptive Fuzzy Control for Dual-Arm Robot With Unknown Kinematics and Dynamics

    Chenguang Yang;Yiming Jiang;Jing Na;Zhijun Li

  • Physical Human–Robot Interaction of a Robotic Exoskeleton By Admittance Control

    Zhijun Li;Bo Huang;Zhifeng Ye;Mingdi Deng

  • Integral Sliding Mode Control: Performance, Modification, and Improvement

    Yongping Pan;Chenguang Yang;Lin Pan;Haoyong Yu

  • Reinforcement Learning Output Feedback NN Control Using Deterministic Learning Technique

    Bin Xu;Chenguang Yang;Zhongke Shi

  • Output Feedback NN Control for Two Classes of Discrete-Time Systems With Unknown Control Directions in a Unified Approach

    Chenguang Yang;Shuzhi Sam Ge;Cheng Xiang;Tianyou Chai

  • Admittance-Based Controller Design for Physical Human–Robot Interaction in the Constrained Task Space

    Wei He;Chengqian Xue;Xinbo Yu;Zhijun Li

  • Neural Control of Robot Manipulators With Trajectory Tracking Constraints and Input Saturation

    Chenguang Yang;Dianye Huang;Wei He;Long Cheng

  • Trajectory Planning and Optimized Adaptive Control for a Class of Wheeled Inverted Pendulum Vehicle Models

    Chenguang Yang;Zhijun Li;Jing Li

  • Adaptive Fuzzy Control for Coordinated Multiple Robots With Constraint Using Impedance Learning

    Linghuan Kong;Wei He;Chenguang Yang;Zhijun Li

  • Adaptive Predictive Control Using Neural Network for a Class of Pure-Feedback Systems in Discrete Time

    Shuzhi Sam Ge;Chenguang Yang;Tong Heng Lee

Frequent Co-Authors

Zhijun Li
Zhijun Li Tongji University
Chun-Yi Su
Chun-Yi Su Concordia University
Wei He
Wei He University of Science and Technology Beijing
Mengyin Fu
Mengyin Fu Nanjing University of Science and Technology
Shuzhi Sam Ge
Shuzhi Sam Ge National University of Singapore
Zhaojie Ju
Zhaojie Ju University of Portsmouth
Tong Heng Lee
Tong Heng Lee National University of Singapore
Angelo Cangelosi
Angelo Cangelosi University of Manchester
Long Cheng
Long Cheng Chinese Academy of Sciences
Jing Na
Jing Na Kunming University of Science and Technology

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For those interested in Electronics and Electrical Engineering in the USA, exploring competency based universities offers a flexible way to gain skills at your own pace. These programs focus on mastering specific competencies over traditional credit hours, making them ideal for students seeking targeted knowledge that directly applies to their career goals.

Military spouses and dependents often face unique challenges when pursuing education. Thankfully, many institutions provide online degrees for military spouses, offering accessible learning options that accommodate frequent relocations and varied schedules.

If you need flexibility, consider programs from the best online colleges with weekly start dates. These colleges allow you to begin courses almost any week of the year, helping you start your education without waiting for traditional semester start times.

For quicker entry into the workforce, short certificate programs that pay well online can provide essential skills and credentials in six months or less. These certificates can complement engineering degrees or serve as standalone qualifications to boost employability.

Best Scientists Citing Chenguang Yang

Trending Scientists

Recently Published Articles