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D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Engineering and Technology 44 5870 5662 311 306 238 6759

Daoyi Dong publications per year

The chart shows the history of publications by Daoyi Dong between 2004 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Daoyi Dong published across 22 years, from 2004 to 2025, averaging 17.2 papers a year. Output peaked at 44 publications in 2024. 85 of the 379 publications appeared in the last two years.

No. of publications
10 20 30 40
Bar chart. Horizontal axis: year, 2004 to 2025. Vertical axis: number of publications, 0 to 44. Peak 44 publications in 2024. 2004: 1 publication 2005: 7 publications 2006: 9 publications 2007: 1 publication 2008: 7 publications 2009: 5 publications 2010: 5 publications 2011: 4 publications 2012: 12 publications 2013: 10 publications 2014: 14 publications 2015: 17 publications 2016: 16 publications 2017: 31 publications 2018: 7 publications 2019: 17 publications 2020: 27 publications 2021: 35 publications 2022: 34 publications 2023: 35 publications 2024: 44 publications 2025: 41 publications
2004 2025

379 publications in total across all disciplines

View publications per year as a table
Daoyi Dong: publications per year, 2004 to 2025
Year Publications
2004 1
2005 7
2006 9
2007 1
2008 7
2009 5
2010 5
2011 4
2012 12
2013 10
2014 14
2015 17
2016 16
2017 31
2018 7
2019 17
2020 27
2021 35
2022 34
2023 35
2024 44
2025 41
Total 379
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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.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: publications, 38–47 to 804+. Vertical axis: number of scientists, 0 to 457. Most scientists, 457, have 148–157 publications. The last bar groups every scientist with 804 publications or more. The highlighted bar, 238–247 publications, is where this scientist sits. 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
38–47 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.

View publications distribution as a table
Number of Engineering and Technology scientists by publication count, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
Publications Scientists This scientist
38–47 20
48–57 35
58–67 96
68–77 135
78–87 190
88–97 259
98–107 283
108–117 369
118–127 341
128–137 386
138–147 372
148–157 457
158–167 415
168–177 407
178–187 421
188–197 378
198–207 403
208–217 317
218–227 346
228–237 321
238–247 260 238
248–257 280
258–267 240
268–277 214
278–287 242
288–297 203
298–307 166
308–317 154
318–327 175
328–337 159
338–347 99
348–357 131
358–367 106
368–377 118
378–387 97
388–397 108
398–407 82
408–417 71
418–427 64
428–437 55
438–447 54
448–457 60
458–467 47
468–477 40
478–487 30
488–497 29
498–507 38
508–517 40
518–527 32
528–537 23
538–547 28
548–557 23
558–567 19
568–577 16
578–587 17
588–597 18
598–607 22
608–617 15
618–627 9
628–637 11
638–647 21
648–657 12
658–667 9
668–677 11
678–687 9
688–697 6
698–707 14
708–717 7
718–727 8
728–737 10
738–747 9
748–757 5
758–767 5
768–777 11
778–787 7
788–797 2
798–803 4
804+ 100
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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.

No. of scientists
100 200 300 400
Bar chart with 78 bars. Horizontal axis: D-Index, 30 to 107+. Vertical axis: number of scientists, 0 to 426. Most scientists, 426, have 42 D-Index. The last bar groups every scientist with 107 D-Index or more. The highlighted bar, 44 D-Index, is where this scientist sits. 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.

View D-Index distribution as a table
Number of Engineering and Technology scientists by D-index, Research.com 2026 ranking edition. Based on 9,796 ranked scientists.
D-Index Scientists This scientist
30 59
31 114
32 129
33 189
34 200
35 262
36 311
37 312
38 350
39 385
40 348
41 362
42 426
43 380
44 310 44
45 341
46 301
47 306
48 271
49 246
50 210
51 253
52 213
53 221
54 195
55 186
56 170
57 167
58 166
59 144
60 152
61 141
62 138
63 131
64 118
65 114
66 119
67 95
68 87
69 77
70 89
71 69
72 54
73 46
74 55
75 54
76 49
77 53
78 46
79 28
80 39
81 36
82 24
83 26
84 36
85 18
86 25
87 19
88 26
89 27
90 23
91 15
92 12
93 9
94 15
95 10
96 13
97 13
98 9
99 7
100 7
101 8
102 7
103 7
104 9
105 6
106 9
107+ 99
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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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