World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
53
Citations
10589
World Ranking
2416
National Ranking
406

Computer Science

D-Index
55
Citations
11198
World Ranking
4349
National Ranking
578

Dongbin Zhao 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 Dongbin Zhao 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: 303 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Dongbin Zhao 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 Dongbin Zhao 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: 53 D-Index — 66th percentile

66% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2020 - IEEE Fellow For contributions to adaptive dynamic programming and reinforcement learning

Overview

Dongbin Zhao is affiliated with the Chinese Academy of Sciences in China. Their research primarily concerns fields within computer science and engineering, with a strong focus on artificial intelligence, computer vision and pattern recognition, automotive engineering, control and systems engineering, and aerospace engineering.

Their work covers several main topics including reinforcement learning in robotics, advanced neural network applications, autonomous vehicle technology and safety, traffic control and management, domain adaptation and few-shot learning, traffic and road safety, and adaptive dynamic programming control.

Dongbin Zhao has published extensively in various academic venues. Their most frequent publication outlets include:

  • arXiv (Cornell University)
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Cognitive and Developmental Systems
  • IEEE Transactions on Systems Man and Cybernetics Systems
  • IEEE Transactions on Cybernetics

Several recent papers authored or co-authored by Dongbin Zhao are:

  • "Artificial intelligence in tongue diagnosis: Using deep convolutional neural network for recognizing unhealthy tongue with tooth-mark," 2020, Computational and Structural Biotechnology Journal
  • "Online Minimax Q Network Learning for Two-Player Zero-Sum Markov Games," 2020, IEEE Transactions on Neural Networks and Learning Systems
  • "Event-Triggered Communication Network With Limited-Bandwidth Constraint for Multi-Agent Reinforcement Learning," 2021, IEEE Transactions on Neural Networks and Learning Systems
  • "CNN-G: Convolutional Neural Network Combined With Graph for Image Segmentation With Theoretical Analysis," 2020, IEEE Transactions on Cognitive and Developmental Systems
  • "BNAS: Efficient Neural Architecture Search Using Broad Scalable Architecture," 2021, IEEE Transactions on Neural Networks and Learning Systems

Their frequent collaborators include:

  • Yaran Chen
  • Yuanheng Zhu
  • Qichao Zhang
  • Haoran Li
  • Zixiang Ding

In 2020, Dongbin Zhao was recognized as an IEEE Fellow for contributions to adaptive dynamic programming and reinforcement learning.

Best Publications

  • Optimal control of unknown nonaffine nonlinear discrete-time systems based on adaptive dynamic programming

    Ding Wang;Derong Liu;Qinglai Wei;Dongbin Zhao

  • Computational Intelligence in Urban Traffic Signal Control: A Survey

    Dongbin Zhao;Yujie Dai;Zhen Zhang

  • Design of a stable sliding-mode controller for a class of second-order underactuated systems

    W. Wang;J. Yi;D. Zhao;D. Liu

  • Adaptive sliding mode fuzzy control for a two-dimensional overhead crane

    Diantong Liu;Jianqiang Yi;Dongbin Zhao;Wei Wang

  • Building Energy Consumption Prediction: An Extreme Deep Learning Approach

    Chengdong Li;Zixiang Ding;Dongbin Zhao;Jianqiang Yi

  • Neural-Network-Based Optimal Control for a Class of Unknown Discrete-Time Nonlinear Systems Using Globalized Dual Heuristic Programming

    Derong Liu;Ding Wang;Dongbin Zhao;Qinglai Wei

  • A computed torque controller for uncertain robotic manipulator systems: Fuzzy approach

    Zuoshi Song;Jianqiang Yi;Dongbin Zhao;Xinchun Li

  • BP neural network prediction-based variable-period sampling approach for networked control systems

    Jianqiang Yi;Qian Wang;Dongbin Zhao;John T. Wen

  • Data-Based Adaptive Critic Designs for Nonlinear Robust Optimal Control With Uncertain Dynamics

    Ding Wang;Derong Liu;Qichao Zhang;Dongbin Zhao

  • Deep Reinforcement Learning-Based Automatic Exploration for Navigation in Unknown Environment

    Haoran Li;Qichao Zhang;Dongbin Zhao

  • Experience Replay for Optimal Control of Nonzero-Sum Game Systems With Unknown Dynamics

    Dongbin Zhao;Qichao Zhang;Ding Wang;Yuanheng Zhu

  • Event-Triggered Optimal Control for Partially Unknown Constrained-Input Systems via Adaptive Dynamic Programming

    Yuanheng Zhu;Dongbin Zhao;Haibo He;Junhong Ji

  • Deep Reinforcement Learning With Visual Attention for Vehicle Classification

    Dongbin Zhao;Yaran Chen;Le Lv

  • Event-Triggered $H_\infty $ Control for Continuous-Time Nonlinear System via Concurrent Learning

    Qichao Zhang;Dongbin Zhao;Yuanheng Zhu

  • StarCraft Micromanagement With Reinforcement Learning and Curriculum Transfer Learning

    Kun Shao;Yuanheng Zhu;Dongbin Zhao

  • Event-Based Robust Control for Uncertain Nonlinear Systems Using Adaptive Dynamic Programming

    Qichao Zhang;Dongbin Zhao;Ding Wang

  • Trajectory Tracking Control of Omnidirectional Wheeled Mobile Manipulators: Robust Neural Network-Based Sliding Mode Approach

    Dong Xu;Dongbin Zhao;Jianqiang Yi;Xiangmin Tan

  • Reinforcement Learning and Deep Learning Based Lateral Control for Autonomous Driving [Application Notes]

    Dong Li;Dongbin Zhao;Qichao Zhang;Yaran Chen

  • Deep reinforcement learning with experience replay based on SARSA

    Dongbin Zhao;Haitao Wang;Kun Shao;Yuanheng Zhu

  • Lane Change Decision-making through Deep Reinforcement Learning with Rule-based Constraints

    Junjie Wang;Qichao Zhang;Dongbin Zhao;Yaran Chen

  • Intelligent methodology for sensing, modeling and control of pulsed GTAW : Part 1 : Bead-on-plate welding

    S. B. Chen;Y. J. Lou;L. Wu;D. B. Zhao

  • A Survey of Deep Reinforcement Learning in Video Games.

    Kun Shao;Zhentao Tang;Yuanheng Zhu;Nannan Li

Frequent Co-Authors

Jianqiang Yi
Jianqiang Yi Chinese Academy of Sciences
Haibo He
Haibo He University of Rhode Island
Derong Liu
Derong Liu University of Illinois at Chicago
Cesare Alippi
Cesare Alippi Polytechnic University of Milan
Ding Wang
Ding Wang Beijing University of Technology
John T. Wen
John T. Wen Rensselaer Polytechnic Institute
Frank L. Lewis
Frank L. Lewis The University of Texas at Arlington
Qinglai Wei
Qinglai Wei Macau University of Science and Technology
Amir Hussain
Amir Hussain Edinburgh Napier University
Simon M. Lucas
Simon M. Lucas Queen Mary University of London

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