World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
61
Citations
14892
World Ranking
1530
National Ranking
251

Yun-Hui Liu 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 Yun-Hui Liu 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: 719 publications — 95th percentile

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

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

Yun-Hui Liu 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 Yun-Hui Liu 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: 61 D-Index — 78th percentile

78% of scientists in this discipline score the same or lower.

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

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Computer vision
  • Electrical engineering

His primary areas of study are Control theory, Control theory, Artificial intelligence, Computer vision and Adaptive control. His Control theory research incorporates elements of Control engineering and Impedance control. His Control theory research includes elements of Stability, Tracking, Position, Robot and Trajectory.

His study in the field of Robotics, Mobile robot and Object also crosses realms of Calibration. His study in the fields of Visual servoing, Image plane and Feature extraction under the domain of Computer vision overlaps with other disciplines such as Multi channel and System of measurement. His Adaptive control research includes themes of Feature and Adaptive algorithm.

His most cited work include:

  • Dynamic sliding PID control for tracking of robot manipulators: theory and experiments (228 citations)
  • Qualitative test and force optimization of 3-D frictional form-closure grasps using linear programming (220 citations)
  • Uncalibrated visual servoing of robots using a depth-independent interaction matrix (209 citations)

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

His scientific interests lie mostly in Artificial intelligence, Computer vision, Robot, Control theory and Control theory. Artificial intelligence connects with themes related to Adaptive algorithm in his study. His Computer vision study incorporates themes from Jacobian matrix and determinant, Odometry and Visual odometry.

His work on Simulation expands to the thematically related Robot. In his study, which falls under the umbrella issue of Control theory, Teleoperation is strongly linked to Control engineering. His Control theory research integrates issues from Control system, Matrix, Convergence, Nonlinear system and Trajectory.

He most often published in these fields:

  • Artificial intelligence (42.29%)
  • Computer vision (33.58%)
  • Robot (30.35%)

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

  • Robot (30.35%)
  • Artificial intelligence (42.29%)
  • Computer vision (33.58%)

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

Yun-Hui Liu spends much of his time researching Robot, Artificial intelligence, Computer vision, Control theory and Control theory. His Robot research is multidisciplinary, relying on both Control engineering, Network topology, Path and Visualization. As part of one scientific family, Yun-Hui Liu deals mainly with the area of Artificial intelligence, narrowing it down to issues related to the Position, and often Estimation theory.

His studies in Computer vision integrate themes in fields like Point, Visual odometry and Robustness. Yun-Hui Liu has included themes like Mobile robot and Tractor in his Control theory study. He has researched Control theory in several fields, including Lyapunov function, Singularity, Jacobian matrix and determinant, Actuator and Robot end effector.

Between 2017 and 2021, his most popular works were:

  • Fourier-Based Shape Servoing: A New Feedback Method to Actively Deform Soft Objects into Desired 2-D Image Contours (50 citations)
  • Iterative learning impedance control for rehabilitation robots driven by series elastic actuators (47 citations)
  • Formation Control of Nonholonomic Mobile Robots Without Position and Velocity Measurements (40 citations)

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

  • Artificial intelligence
  • Computer vision
  • Electrical engineering

Robot, Artificial intelligence, Control theory, Control theory and Computer vision are his primary areas of study. The various areas that Yun-Hui Liu examines in his Robot study include Visualization and Eye tracking. Many of his studies on Artificial intelligence apply to Machine learning as well.

His study in Control theory is interdisciplinary in nature, drawing from both Deformation control and Mobile robot. His Control theory study integrates concerns from other disciplines, such as Control system, Linear approximation, Continuum, Lyapunov function and Visual servoing. His Computer vision research incorporates themes from Representation, Position and Robustness.

Best Publications

  • Dynamic sliding PID control for tracking of robot manipulators: theory and experiments

    V. Parra-Vega;S. Arimoto;Yun-Hui Liu;G. Hirzinger

  • Uncalibrated visual servoing of robots using a depth-independent interaction matrix

    Yun-Hui Liu;Hesheng Wang;Chengyou Wang;Kin Kwan Lam

  • Qualitative test and force optimization of 3-D frictional form-closure grasps using linear programming

    Yun-Hui Liu;Mei Wang

  • LPD-Net: 3D Point Cloud Learning for Large-Scale Place Recognition and Environment Analysis

    Zhe Liu;Shunbo Zhou;Chuanzhe Suo;Peng Yin

  • Enclosing a target by nonholonomic mobile robots with bearing-only measurements

    Ronghao Zheng;Yunhui Liu;Dong Sun

  • Self-supervised Video Representation Learning by Pace Prediction

    Jiangliu Wang;Jianbo Jiao;Yun-Hui Liu

  • Self-Supervised Spatio-Temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics

    Jiangliu Wang;Jianbo Jiao;Linchao Bao;Shengfeng He

  • Automatic 3-D Manipulation of Soft Objects by Robotic Arms With an Adaptive Deformation Model

    David Navarro-Alarcon;Hiu Man Yip;Zerui Wang;Yun-Hui Liu

  • Path planning using a tangent graph for mobile robots among polygonal and curved obstacles

    Yun-Hui Liu;Suguru Arimoto

  • Adaptive Visual Servoing Using Point and Line Features With an Uncalibrated Eye-in-Hand Camera

    Hesheng Wang;Yun-Hui Liu;Dongxiang Zhou

  • Computing n-Finger Form-Closure Grasps on Polygonal Objects

    Yun-Hui Liu

  • Haptic information in Internet-based teleoperation

    I. Elhajj;N. Xi;Wai Keung Fung;Yun Hui Liu

  • Iterative learning impedance control for rehabilitation robots driven by series elastic actuators

    Xiang Li;Yun-Hui Liu;Haoyong Yu

  • An algorithm for extrinsic parameters calibration of a camera and a laser range finder using line features

    Ganhua Li;Yunhui Liu;Li Dong;Xuanping Cai

  • A complete and efficient algorithm for searching 3-D form-closure grasps in the discrete domain

    Yun-Hui Liu;Miu-Ling Lam;D. Ding

  • Fourier-Based Shape Servoing: A New Feedback Method to Actively Deform Soft Objects into Desired 2-D Image Contours

    David Navarro-Alarcon;Yun-Hui Liu

  • Model-Free Visually Servoed Deformation Control of Elastic Objects by Robot Manipulators

    David Navarro-Alarcon;Yun-Hui Liu;Jose Guadalupe Romero;Peng Li

  • Visual Servoing Trajectory Tracking of Nonholonomic Mobile Robots Without Direct Position Measurement

    Kai Wang;Yunhui Liu;Luyang Li

  • Distributed Estimation and Control for Leader-Following Formations of Nonholonomic Mobile Robots

    Zhiqiang Miao;Yun-Hui Liu;Yaonan Wang;Guo Yi

  • Dynamic Visual Tracking for Manipulators Using an Uncalibrated Fixed Camera

    Hesheng Wang;Yun-Hui Liu;Dongxiang Zhou

  • Supermedia-enhanced Internet-based telerobotics

    I. Elhajj;Ning Xi;Wai Keung Fung;Yun-Hui Liu

Frequent Co-Authors

Suguru Arimoto
Suguru Arimoto University of Toyama
Wen J. Li
Wen J. Li City University of Hong Kong
Ning Xi
Ning Xi University of Hong Kong
Toshio Fukuda
Toshio Fukuda Nagoya University
Yun Kwok Wing
Yun Kwok Wing Chinese University of Hong Kong
James K. Mills
James K. Mills University of Toronto
Yasuhisa Hasegawa
Yasuhisa Hasegawa Nagoya University
Yangsheng Xu
Yangsheng Xu Chinese University of Hong Kong, Shenzhen
Shugen Ma
Shugen Ma Ritsumeikan University
Jindong Tan
Jindong Tan University of Tennessee at Knoxville

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

Pursuing studies in Electronics and Electrical Engineering opens doors to various educational and career opportunities, many of which offer flexible scheduling options. For students balancing work or personal commitments, enrolling in online colleges with flexible start dates can provide the adaptability needed to begin courses at convenient times throughout the year.

For those looking to quickly enhance their skills and enter the job market, 6 month certificate programs that pay well offer accelerated learning paths focused on industry-relevant expertise. These short-term credentials often complement a broader engineering background by focusing on specialized topics like circuit design or automation.

Career pathways in this field also accommodate different personality types. Individuals who prefer independent or low-interaction roles can thrive by exploring careers for introverts that emphasize problem-solving, research, and technical development within electronics and electrical engineering.

Additionally, for engineers aspiring to management positions, pursuing an accelerated online project management degree can equip them with leadership and organizational skills required to manage complex engineering projects efficiently.

Best Scientists Citing Yun-Hui Liu

Trending Scientists