World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
44
Citations
6759
World Ranking
5870
National Ranking
311

Daoyi Dong 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 Daoyi Dong 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: 238 publications — 61st percentile

61% of scientists in this discipline score the same or lower.

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

Daoyi Dong 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 Daoyi Dong 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: 44 D-Index — 42nd percentile

42% of scientists in this discipline score the same or lower.

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

Overview

Daoyi Dong is affiliated with the University of New South Wales in Australia. Their research spans multiple fields including Computer Science, Physics and Astronomy, and Engineering, with a particular emphasis on Artificial Intelligence and Quantum-related disciplines.

Their recent papers reflect active engagement with topics at the intersection of quantum technology, control, and machine learning. Notable publications include:

  • Microgrids: A review, outstanding issues and future trends (2023) published in Energy Strategy Reviews
  • Quantum reinforcement learning during human decision-making (2020) in Nature Human Behaviour
  • Deep Reinforcement Learning With Quantum-Inspired Experience Replay (2021) in IEEE Transactions on Cybernetics
  • Path Planning for Cellular-Connected UAV: A DRL Solution With Quantum-Inspired Experience Replay (2022) in IEEE Transactions on Wireless Communications
  • Quantum estimation, control and learning: Opportunities and challenges (2022) in Annual Reviews in Control

Daoyi Dong has published a book titled Learning and Robust Control in Quantum Technology (2023) under the Communications and Control Engineering series. This reflects an integration of control theory with quantum technology.

Their research topics cover a broad range of quantum science and engineering areas, including:

  • Quantum Information and Cryptography
  • Quantum Computing Algorithms and Architecture
  • Quantum Mechanics and Applications
  • Smart Grid Energy Management
  • Laser-Matter Interactions and Applications
  • Spectroscopy and Quantum Chemical Studies
  • Neural Networks and Reservoir Computing

Frequent co-authors contributing substantially to Daoyi Dong's research include:

  • Ian R. Petersen
  • Huadong Mo
  • Hailan Ma
  • Chunlin Chen
  • Kathleen Kramer

Daoyi Dong's publications are frequently found in the following venues:

  • arXiv (Cornell University)
  • IEEE Transactions on Cybernetics
  • IEEE Transactions on Neural Networks and Learning Systems
  • Automatica
  • Physical Review A

Their subfields of study emphasize both foundational and applied areas of quantum physics and artificial intelligence, including:

  • Artificial Intelligence
  • Atomic and Molecular Physics and Optics
  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Statistical and Nonlinear Physics

Best Publications

  • Quantum control theory and applications: a survey

    Daoyi Dong;Ian R. Petersen

  • Quantum Reinforcement Learning

    Daoyi Dong;Chunlin Chen;Hanxiong Li;Tzyh-Jong Tarn

  • Fidelity-Based Probabilistic Q-Learning for Control of Quantum Systems

    Chunlin Chen;Daoyi Dong;Han-Xiong Li;Jian Chu

  • Quantum State Tomography via Linear Regression Estimation

    Bo Qi;Zhibo Hou;L i Li;Daoyi Dong

  • Sliding mode control of two-level quantum systems

    Daoyi Dong;Ian R. Petersen

  • Sampling-based learning control of inhomogeneous quantum ensembles

    Chunlin Chen;Chunlin Chen;Daoyi Dong;Ruixing Long;Ian R. Petersen

  • Sliding mode control of quantum systems

    Daoyi Dong;Ian R Petersen

  • Adaptive quantum state tomography via linear regression estimation: Theory and two-qubit experiment

    Bo Qi;Bo Qi;Zhibo Hou;Yuanlong Wang;Daoyi Dong

  • Learning robust and high-precision quantum controls

    Re-Bing Wu;Haijin Ding;Daoyi Dong;Xiaoting Wang

  • Optimal Lyapunov-based quantum control for quantum systems

    Shao-Chen Hou;M. A Khan;X. X. Yi;Daoyi Dong

  • Self-Paced Prioritized Curriculum Learning With Coverage Penalty in Deep Reinforcement Learning

    Zhipeng Ren;Daoyi Dong;Huaxiong Li;Chunlin Chen

  • Full reconstruction of a 14-qubit state within four hours

    Zhibo Hou;Han Sen Zhong;Ye Tian;Daoyi Dong

  • Recursively Adaptive Quantum State Tomography: Theory and Two-qubit Experiment

    Bo Qi;Zhibo Hou;Yuanlong Wang;Daoyi Dong

  • Quantum reinforcement learning during human decision-making

    Ji-An Li;Daoyi Dong;Zhengde Wei;Zhengde Wei;Ying Liu

  • Deep Reinforcement Learning With Quantum-Inspired Experience Replay.

    Qing Wei;Hailan Ma;Chunlin Chen;Daoyi Dong

  • Robust Quantum-Inspired Reinforcement Learning for Robot Navigation

    Daoyi Dong;Chunlin Chen;Jian Chu;Tzyh-Jong Tarn

  • Path Planning for Cellular-Connected UAV: A DRL Solution with Quantum-Inspired Experience Replay.

    Yuanjian Li;A. Hamid Aghvami;Daoyi Dong

  • Rapid Lyapunov control of finite-dimensional quantum systems

    Sen Kuang;Daoyi Dong;Ian R. Petersen

  • A Quantum Hamiltonian Identification Algorithm: Computational Complexity and Error Analysis

    Yuanlong Wang;Daoyi Dong;Bo Qi;Jun Zhang

  • Hybrid Control for Robot Navigation - A Hierarchical Q-Learning Algorithm

    Chunlin Chen;Han-Xiong Li;Daoyi Dong

  • Incoherent Control of Quantum Systems With Wavefunction-Controllable Subspaces via Quantum Reinforcement Learning

    Daoyi Dong;Chunlin Chen;Tzyh-Jong Tarn;A. Pechen

  • Learning-Based Quantum Robust Control: Algorithm, Applications, and Experiments

    Daoyi Dong;Xi Xing;Hailan Ma;Chunlin Chen

  • Robust manipulation of superconducting qubits in the presence of fluctuations

    Daoyi Dong;Chunlin Chen;Bo Qi;Ian R. Petersen

  • Quantum robot: structure, algorithms and applications

    Daoyi Dong;Chunlin Chen;Chenbin Zhang;Zonghai Chen

Frequent Co-Authors

Ian R. Petersen
Ian R. Petersen Australian National University
Herschel Rabitz
Herschel Rabitz Princeton University
Zonghai Chen
Zonghai Chen Argonne National Laboratory
Franco Nori
Franco Nori University of Michigan–Ann Arbor
Guang-Can Guo
Guang-Can Guo University of Science and Technology of China
Tzyh-Jong Tarn
Tzyh-Jong Tarn Washington University in St. Louis
Han-Xiong Li
Han-Xiong Li City University of Hong Kong
Wei Cui
Wei Cui Tsinghua University
Steven X. Ding
Steven X. Ding University of Duisburg-Essen
Karl Henrik Johansson
Karl Henrik Johansson Royal Institute of Technology

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