World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
41
Citations
5497
World Ranking
7086
National Ranking
1303

Deyuan Meng publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Deyuan Meng sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 220 publications — 55th percentile

55% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Deyuan Meng D-index placement in Engineering and Technology in 2026

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

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 41 D-Index — 31st percentile

31% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Deyuan Meng is affiliated with Beihang University in China and focuses research efforts primarily within the fields of Engineering and Computer Science. Their research contributions span various interconnected subfields including Control and Systems Engineering, Computer Networks and Communications, Statistical and Nonlinear Physics, Mechanical Engineering, and Electrical and Electronic Engineering.

Their main research topics include:

  • Iterative Learning Control Systems
  • Distributed Control Multi-Agent Systems
  • Neural Networks Stability and Synchronization
  • Advanced Control Systems Optimization
  • Opinion Dynamics and Social Influence
  • Control Systems and Identification
  • Advanced Measurement and Metrology Techniques

Key recent publications by Deyuan Meng include:

  • Robust Optimization-Based Iterative Learning Control for Nonlinear Systems With Nonrepetitive Uncertainties, 2021, IEEE/CAA Journal of Automatica Sinica
  • Convergence Analysis of Robust Iterative Learning Control Against Nonrepetitive Uncertainties: System Equivalence Transformation, 2020, IEEE Transactions on Neural Networks and Learning Systems
  • Design and Analysis of Data-Driven Learning Control: An Optimization-Based Approach, 2021, IEEE Transactions on Neural Networks and Learning Systems

The scholar has contributed book publications, including:

  • Disagreement Behavior Analysis of Signed Networks, 2022, Springer Nature

Frequent publication venues where their work appears consist of:

  • Automatica
  • IEEE Transactions on Automatic Control
  • IEEE Transactions on Control of Network Systems
  • arXiv (Cornell University)
  • IEEE Transactions on Cybernetics

Deyuan Meng collaborates regularly with several researchers who appear frequently as co-authors:

  • Yuxin Wu
  • Mingjun Du
  • Jingyao Zhang
  • Kaiquan Cai
  • Qiang Song

Best Publications

  • Interval Bipartite Consensus of Networked Agents Associated With Signed Digraphs

    Deyuan Meng;Mingjun Du;Yingmin Jia

  • Robust Iterative Learning Control for Nonrepetitive Uncertain Systems

    Deyuan Meng;Kevin L. Moore

  • Bipartite containment tracking of signed networks

    Deyuan Meng

  • Finite-Time Consensus for Multiagent Systems With Cooperative and Antagonistic Interactions

    Deyuan Meng;Yingmin Jia;Junping Du

  • On iterative learning algorithms for the formation control of nonlinear multi-agent systems

    Deyuan Meng;Yingmin Jia;Junping Du;Jun Zhang

  • Iterative learning approaches to design finite-time consensus protocols for multi-agent systems

    Deyuan Meng;Yingmin Jia

  • Learning to cooperate

    Deyuan Meng;Kevin L. Moore

  • Formation control for multi-agent systems through an iterative learning design approach

    Deyuan Meng;Yingmin Jia

  • Robust Consensus Tracking Control for Multiagent Systems With Initial State Shifts, Disturbances, and Switching Topologies

    Deyuan Meng;Yingmin Jia;Junping Du

  • Adaptive Iterative Learning Control for High-Speed Train: A Multi-Agent Approach

    Unknown

  • Tracking control over a finite interval for multi-agent systems with a time-varying reference trajectory☆

    Deyuan Meng;Yingmin Jia;Junping Du;Fashan Yu

  • Scaled Consensus Problems on Switching Networks

    Deyuan Meng;Yingmin Jia

  • Convergence of iterative learning control for SISO nonrepetitive systems subject to iteration-dependent uncertainties

    Deyuan Meng;Kevin L. Moore

  • Robust Consensus Algorithms for Multiscale Coordination Control of Multivehicle Systems With Disturbances

    Unknown

  • Nonlinear finite-time bipartite consensus protocol for multi-agent systems associated with signed graphs

    Deyuan Meng;Yingmin Jia;Junping Du

  • Robust Optimization-Based Iterative Learning Control for Nonlinear Systems With Nonrepetitive Uncertainties

    Unknown

  • Finite-time consensus for multi-agent systems via terminal feedback iterative learning

    D. Meng;Y. Jia

  • Robust Discrete-Time Iterative Learning Control for Nonlinear Systems With Varying Initial State Shifts

    Deyuan Meng;Yingmin Jia;Junping Du;Shiying Yuan

  • Deterministic Convergence for Learning Control Systems Over Iteration-Dependent Tracking Intervals

    Unknown

  • Robust cooperative learning control for directed networks with nonlinear dynamics

    Deyuan Meng;Kevin L. Moore

  • Signed-average consensus for networks of agents: a nonlinear fixed-time convergence protocol

    Deyuan Meng;Zongyu Zuo

  • Robust iterative learning control design for uncertain time-delay systems based on a performance index

    D. Meng;Y. Jia;J. Du;F. Yu

  • Extended Structural Balance Theory and Method for Cooperative–Antagonistic Networks

    Deyuan Meng;Mingjun Du;Yuxin Wu

  • Uniform convergence for signed networks under directed switching topologies

    Deyuan Meng;Ziyang Meng;Yiguang Hong

  • Disagreement of Hierarchical Opinion Dynamics with Changing Antagonisms

    Deyuan Meng;Ziyang Meng;Yiguang Hong

  • High-precision formation control of nonlinear multi-agent systems with switching topologies: A learning approach

    Deyuan Meng;Yingmin Jia;Junping Du;Jun Zhang

  • On exponential stability of switched homogeneous positive systems of degree one

    Yao Zou;Ziyang Meng;Deyuan Meng

  • Learning control for time-delay systems with iteration-varying uncertainty: a Smith predictor-based approach

    D. Meng;Y. Jia;J. Du;F. Yu

  • Fixed-time consensus for multi-agent systems under directed and switching interaction topology

    Zongyu Zuo;Wen Yang;Lin Tie;Deyuan Meng

  • Feedback approach to design fast iterative learning controller for a class of time-delay systems

    D. Meng;Y. Jia;J. Du;S. Yuan

Frequent Co-Authors

Kevin L. Moore
Kevin L. Moore Colorado School of Mines
Ziyang Meng
Ziyang Meng Tsinghua University
Yingmin Jia
Yingmin Jia Beihang University
Zheng-Guang Wu
Zheng-Guang Wu Zhejiang University
Junping Du
Junping Du Beijing University of Posts and Telecommunications
Yiguang Hong
Yiguang Hong Chinese Academy of Sciences

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