World's Best Scientists 2026 revealed!
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Dongpu Cao
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Mechanical and Aerospace Engineering
Canada
2026

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Mechanical and Aerospace Engineering 85 153 140 9 9 373 24864

Dongpu Cao publications per year

The chart shows the history of publications by Dongpu Cao between 2003 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Dongpu Cao published across 23 years, from 2003 to 2025, averaging 17.4 papers a year. Output peaked at 75 publications in 2020. 25 of the 401 publications appeared in the last two years.

No. of publications
25 50 75
Bar chart. Horizontal axis: year, 2003 to 2025. Vertical axis: number of publications, 0 to 75. Peak 75 publications in 2020. 2003: 1 publication 2004: 0 publications 2005: 3 publications 2006: 1 publication 2007: 4 publications 2008: 7 publications 2009: 4 publications 2010: 7 publications 2011: 15 publications 2012: 6 publications 2013: 7 publications 2014: 4 publications 2015: 13 publications 2016: 17 publications 2017: 22 publications 2018: 40 publications 2019: 45 publications 2020: 75 publications 2021: 51 publications 2022: 28 publications 2023: 26 publications 2024: 17 publications 2025: 8 publications
2003 2025

401 publications in total across all disciplines

View publications per year as a table
Dongpu Cao: publications per year, 2003 to 2025
Year Publications
2003 1
2004 0
2005 3
2006 1
2007 4
2008 7
2009 4
2010 7
2011 15
2012 6
2013 7
2014 4
2015 13
2016 17
2017 22
2018 40
2019 45
2020 75
2021 51
2022 28
2023 26
2024 17
2025 8
Total 401
Download as CSV

Dongpu Cao publication distribution in Mechanical and Aerospace Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Mechanical and Aerospace Engineering in 2026. The highlighted bar marks where Dongpu Cao sits on this spectrum.

No. of scientists
50 100 150
Bar chart with 63 bars. Horizontal axis: publications, 47–56 to 659+. Vertical axis: number of scientists, 0 to 155. Most scientists, 155, have 147–156 publications. The last bar groups every scientist with 659 publications or more. The highlighted bar, 367–376 publications, is where this scientist sits. 47–56 publications: 10 scientists 57–66 publications: 23 scientists 67–76 publications: 32 scientists 77–86 publications: 62 scientists 87–96 publications: 67 scientists 97–106 publications: 91 scientists 107–116 publications: 113 scientists 117–126 publications: 115 scientists 127–136 publications: 130 scientists 137–146 publications: 140 scientists 147–156 publications: 155 scientists 157–166 publications: 132 scientists 167–176 publications: 133 scientists 177–186 publications: 130 scientists 187–196 publications: 140 scientists 197–206 publications: 115 scientists 207–216 publications: 125 scientists 217–226 publications: 117 scientists 227–236 publications: 99 scientists 237–246 publications: 92 scientists 247–256 publications: 100 scientists 257–266 publications: 95 scientists 267–276 publications: 88 scientists 277–286 publications: 77 scientists 287–296 publications: 74 scientists 297–306 publications: 74 scientists 307–316 publications: 62 scientists 317–326 publications: 70 scientists 327–336 publications: 59 scientists 337–346 publications: 58 scientists 347–356 publications: 45 scientists 357–366 publications: 44 scientists 367–376 publications: 36 scientists 377–386 publications: 41 scientists 387–396 publications: 32 scientists 397–406 publications: 23 scientists 407–416 publications: 28 scientists 417–426 publications: 27 scientists 427–436 publications: 25 scientists 437–446 publications: 23 scientists 447–456 publications: 23 scientists 457–466 publications: 20 scientists 467–476 publications: 12 scientists 477–486 publications: 24 scientists 487–496 publications: 18 scientists 497–506 publications: 12 scientists 507–516 publications: 13 scientists 517–526 publications: 21 scientists 527–536 publications: 12 scientists 537–546 publications: 8 scientists 547–556 publications: 16 scientists 557–566 publications: 3 scientists 567–576 publications: 11 scientists 577–586 publications: 6 scientists 587–596 publications: 5 scientists 597–606 publications: 6 scientists 607–616 publications: 7 scientists 617–626 publications: 7 scientists 627–636 publications: 10 scientists 637–646 publications: 4 scientists 647–656 publications: 3 scientists 657–658 publications: 2 scientists 659+ publications: 100 scientists
47–56 publications 659+

This scientist: 373 publications — 84th percentile

84% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 659 publications or more.

View publications distribution as a table
Number of Mechanical and Aerospace Engineering scientists by publication count, Research.com 2026 ranking edition. Based on 3,445 ranked scientists.
Publications Scientists This scientist
47–56 10
57–66 23
67–76 32
77–86 62
87–96 67
97–106 91
107–116 113
117–126 115
127–136 130
137–146 140
147–156 155
157–166 132
167–176 133
177–186 130
187–196 140
197–206 115
207–216 125
217–226 117
227–236 99
237–246 92
247–256 100
257–266 95
267–276 88
277–286 77
287–296 74
297–306 74
307–316 62
317–326 70
327–336 59
337–346 58
347–356 45
357–366 44
367–376 36 373
377–386 41
387–396 32
397–406 23
407–416 28
417–426 27
427–436 25
437–446 23
447–456 23
457–466 20
467–476 12
477–486 24
487–496 18
497–506 12
507–516 13
517–526 21
527–536 12
537–546 8
547–556 16
557–566 3
567–576 11
577–586 6
587–596 5
597–606 6
607–616 7
617–626 7
627–636 10
637–646 4
647–656 3
657–658 2
659+ 100
Download as CSV

Dongpu Cao D-index placement in Mechanical and Aerospace Engineering in 2026

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

No. of scientists
50 100 150
Bar chart with 64 bars. Horizontal axis: D-Index, 30 to 93+. Vertical axis: number of scientists, 0 to 189. Most scientists, 189, have 34 D-Index. The last bar groups every scientist with 93 D-Index or more. The highlighted bar, 85 D-Index, is where this scientist sits. 30 D-Index: 83 scientists 31 D-Index: 113 scientists 32 D-Index: 144 scientists 33 D-Index: 153 scientists 34 D-Index: 189 scientists 35 D-Index: 158 scientists 36 D-Index: 139 scientists 37 D-Index: 127 scientists 38 D-Index: 130 scientists 39 D-Index: 126 scientists 40 D-Index: 104 scientists 41 D-Index: 100 scientists 42 D-Index: 107 scientists 43 D-Index: 101 scientists 44 D-Index: 103 scientists 45 D-Index: 79 scientists 46 D-Index: 88 scientists 47 D-Index: 70 scientists 48 D-Index: 83 scientists 49 D-Index: 44 scientists 50 D-Index: 64 scientists 51 D-Index: 56 scientists 52 D-Index: 50 scientists 53 D-Index: 48 scientists 54 D-Index: 58 scientists 55 D-Index: 52 scientists 56 D-Index: 48 scientists 57 D-Index: 42 scientists 58 D-Index: 34 scientists 59 D-Index: 42 scientists 60 D-Index: 37 scientists 61 D-Index: 42 scientists 62 D-Index: 44 scientists 63 D-Index: 22 scientists 64 D-Index: 33 scientists 65 D-Index: 29 scientists 66 D-Index: 23 scientists 67 D-Index: 29 scientists 68 D-Index: 24 scientists 69 D-Index: 19 scientists 70 D-Index: 34 scientists 71 D-Index: 26 scientists 72 D-Index: 19 scientists 73 D-Index: 18 scientists 74 D-Index: 19 scientists 75 D-Index: 14 scientists 76 D-Index: 19 scientists 77 D-Index: 8 scientists 78 D-Index: 18 scientists 79 D-Index: 16 scientists 80 D-Index: 12 scientists 81 D-Index: 17 scientists 82 D-Index: 11 scientists 83 D-Index: 16 scientists 84 D-Index: 7 scientists 85 D-Index: 9 scientists 86 D-Index: 8 scientists 87 D-Index: 6 scientists 88 D-Index: 6 scientists 89 D-Index: 7 scientists 90 D-Index: 10 scientists 91 D-Index: 4 scientists 92 D-Index: 4 scientists 93+ D-Index: 100 scientists
30 D-Index 93+

This scientist: 85 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 93 D-Index or more.

View D-Index distribution as a table
Number of Mechanical and Aerospace Engineering scientists by D-index, Research.com 2026 ranking edition. Based on 3,445 ranked scientists.
D-Index Scientists This scientist
30 83
31 113
32 144
33 153
34 189
35 158
36 139
37 127
38 130
39 126
40 104
41 100
42 107
43 101
44 103
45 79
46 88
47 70
48 83
49 44
50 64
51 56
52 50
53 48
54 58
55 52
56 48
57 42
58 34
59 42
60 37
61 42
62 44
63 22
64 33
65 29
66 23
67 29
68 24
69 19
70 34
71 26
72 19
73 18
74 19
75 14
76 19
77 8
78 18
79 16
80 12
81 17
82 11
83 16
84 7
85 9 85
86 8
87 6
88 6
89 7
90 10
91 4
92 4
93+ 100
Download as CSV

Research.com Recognitions

  • 2026 - Research.com Mechanical and Aerospace Engineering in Canada Leader Award

Overview

Dongpu Cao is affiliated with the University of Waterloo in Canada. Their research primarily spans the fields of Engineering and Computer Science, with a substantial focus on Automotive Engineering, Control and Systems Engineering, and Computer Vision and Pattern Recognition. Dongpu Cao's body of work addresses several advanced topics relevant to autonomous and intelligent vehicles.

The main topics covered by their research include autonomous vehicle technology and safety, traffic control and management, vehicle dynamics and control systems, advanced neural network applications, human-automation interaction and safety, traffic and road safety, and vehicular ad hoc networks (VANETs).

Dongpu Cao has authored multiple papers, with recent publications including:

  • "Future Directions of Intelligent Vehicles: Potentials, Possibilities, and Perspectives" (2022) published in IEEE Transactions on Intelligent Vehicles
  • "Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review" (2020) in IEEE Transactions on Neural Networks and Learning Systems
  • "Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review" (2021) in IEEE Transactions on Intelligent Transportation Systems
  • "Deep Neural Network Based Vehicle and Pedestrian Detection for Autonomous Driving: A Survey" (2021) in IEEE Transactions on Intelligent Transportation Systems
  • "A deep learning based image enhancement approach for autonomous driving at night" (2020) in Knowledge-Based Systems

Their frequent coauthors include Chen Lv, Yang Xing, Teng Liu, Daxin Tian, and Guofa Li.

Dongpu Cao's publications appear consistently in venues such as IEEE Transactions on Intelligent Transportation Systems, arXiv (Cornell University), IEEE Transactions on Vehicular Technology, IEEE Transactions on Intelligent Vehicles, and IEEE/CAA Journal of Automatica Sinica.

In addition to journal articles, Dongpu Cao has contributed to book publications, with a noted book titled "Cyber-Physical Vehicle Systems" published in 2020 by Morgan & Claypool Publishers.

Best Publications

  • Stability and Scalability of Homogeneous Vehicular Platoon: Study on the Influence of Information Flow Topologies

    Yang Zheng;Shengbo Eben Li;Jianqiang Wang;Dongpu Cao

  • Energy Management in Plug-in Hybrid Electric Vehicles: Recent Progress and a Connected Vehicles Perspective

    Clara Marina Martinez;Xiaosong Hu;Dongpu Cao;Efstathios Velenis

  • Driving Style Recognition for Intelligent Vehicle Control and Advanced Driver Assistance: A Survey

    Clara Marina Martinez;Mira Heucke;Fei-Yue Wang;Bo Gao

  • Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

    Ying Li;Lingfei Ma;Zilong Zhong;Fei Liu

  • Battery Health Prognosis for Electric Vehicles Using Sample Entropy and Sparse Bayesian Predictive Modeling

    Xiaosong Hu;Jiuchun Jiang;Dongpu Cao;Bo Egardt

  • Deep Learning for Image and Point Cloud Fusion in Autonomous Driving: A Review

    Yaodong Cui;Ren Chen;Wenbo Chu;Long Chen

  • Energy management strategies of connected HEVs and PHEVs: Recent progress and outlook

    Fengqi Zhang;Xiaosong Hu;Reza Langari;Dongpu Cao

  • Editors’ perspectives: road vehicle suspension design, dynamics, and control

    Dongpu Cao;Xubin Song;Mehdi Ahmadian

  • Reinforcement Learning Optimized Look-Ahead Energy Management of a Parallel Hybrid Electric Vehicle

    Teng Liu;Xiaosong Hu;Shengbo Eben Li;Dongpu Cao

  • Driver Activity Recognition for Intelligent Vehicles: A Deep Learning Approach

    Yang Xing;Chen Lv;Huaji Wang;Dongpu Cao

  • A Motion Planning and Tracking Framework for Autonomous Vehicles Based on Artificial Potential Field Elaborated Resistance Network Approach

    Yanjun Huang;Haitao Ding;Yubiao Zhang;Hong Wang

  • Dynamic path planning for autonomous driving on various roads with avoidance of static and moving obstacles

    Xuemin Hu;Long Chen;Bo Tang;Dongpu Cao

  • Levenberg–Marquardt Backpropagation Training of Multilayer Neural Networks for State Estimation of a Safety-Critical Cyber-Physical System

    Chen Lv;Yang Xing;Junzhi Zhang;Xiaoxiang Na

  • Real-Time Trajectory Planning for Autonomous Urban Driving: Framework, Algorithms, and Verifications

    Xiaohui Li;Zhenping Sun;Dongpu Cao;Zhen He

  • A theoretical and computational study of lithium-ion battery thermal management for electric vehicles using heat pipes

    Angelo Greco;Dongpu Cao;Xi Jiang;Hong Yang

  • Driving-Style-Based Codesign Optimization of an Automated Electric Vehicle: A Cyber-Physical System Approach

    Chen Lv;Xiaosong Hu;Alberto Sangiovanni-Vincentelli;Yutong Li

  • Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles

    Xiaohui Li;Zhenping Sun;Dongpu Cao;Daxue Liu

  • Parallel driving in CPSS: a unified approach for transport automation and vehicle intelligence

    Fei-Yue Wang;Nan-Ning Zheng;Dongpu Cao;Clara Marina Martinez

  • Driver Lane Change Intention Inference for Intelligent Vehicles: Framework, Survey, and Challenges

    Yang Xing;Chen Lv;Huaji Wang;Hong Wang

  • Integrated Optimization of Battery Sizing, Charging, and Power Management in Plug-In Hybrid Electric Vehicles

    Xiaosong Hu;Scott J. Moura;Nikolce Murgovski;Bo Egardt

  • Deep Learning for LiDAR Point Clouds in Autonomous Driving: A Review

    Ying Li;Lingfei Ma;Zilong Zhong;Fei Liu

Frequent Co-Authors

Chen Lv
Chen Lv Nanyang Technological University
Fei-Yue Wang
Fei-Yue Wang Chinese Academy of Sciences
Yang Xing
Yang Xing Cranfield University
Subhash Rakheja
Subhash Rakheja Concordia University
Efstathios Velenis
Efstathios Velenis Cranfield University
Amir Khajepour
Amir Khajepour University of Waterloo
Xiaosong Hu
Xiaosong Hu Chongqing University
Hong Chen
Hong Chen Tongji University
Chun-Yi Su
Chun-Yi Su Concordia University
Nanning Zheng
Nanning Zheng Xi'an Jiaotong University

External Links

Personal website of Dongpu Cao Google Scholar page

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Related Online Degrees & Career Pathways

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Overall, considering related online degrees and career pathways can enhance one’s credentials and open doors beyond traditional engineering careers.

Best Scientists Citing Dongpu Cao

Nong Zhang

Nong Zhang

University of Technology Sydney

Publications: 58

Xiaosong Hu

Xiaosong Hu

Chongqing University

Publications: 37

Keqiang Li

Keqiang Li

Tsinghua University

Publications: 29

Shengbo Eben Li

Shengbo Eben Li

Tsinghua University

Publications: 29

Hong Chen

Hong Chen

Tongji University

Publications: 27

Xiangyu Wang

Xiangyu Wang

Curtin University

Publications: 25

Amir Khajepour

Amir Khajepour

University of Waterloo

Publications: 24

Chen Lv

Chen Lv

Nanyang Technological University

Publications: 21

Fei-Yue Wang

Fei-Yue Wang

Chinese Academy of Sciences

Publications: 20

Subhash Rakheja

Subhash Rakheja

Concordia University

Publications: 19

Jianqiang Wang

Jianqiang Wang

Central South University

Publications: 18

Haiping Du

Haiping Du

University of Wollongong

Publications: 17

Junmin Wang

Junmin Wang

The University of Texas at Austin

Publications: 17

Weichao Sun

Weichao Sun

Harbin Institute of Technology

Publications: 14

Yingfeng Cai

Yingfeng Cai

Tongji University

Publications: 14

Jian Song

Jian Song

Tsinghua University

Publications: 12

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