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Ming-Song Chen

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Materials Science 50 10340 9984 2904 2891 101 7472

Ming-Song Chen publications per year

The chart shows the history of publications by Ming-Song Chen between 2008 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Ming-Song Chen published across 18 years, from 2008 to 2025, averaging 7.6 papers a year. Output peaked at 20 publications in 2016. 27 of the 136 publications appeared in the last two years.

No. of publications
5 10 15 20
Bar chart. Horizontal axis: year, 2008 to 2025. Vertical axis: number of publications, 0 to 20. Peak 20 publications in 2016. 2008: 6 publications 2009: 7 publications 2010: 2 publications 2011: 2 publications 2012: 2 publications 2013: 4 publications 2014: 3 publications 2015: 5 publications 2016: 20 publications 2017: 8 publications 2018: 9 publications 2019: 9 publications 2020: 4 publications 2021: 9 publications 2022: 10 publications 2023: 9 publications 2024: 15 publications 2025: 12 publications
2008 2025

136 publications in total across all disciplines

View publications per year as a table
Ming-Song Chen: publications per year, 2008 to 2025
Year Publications
2008 6
2009 7
2010 2
2011 2
2012 2
2013 4
2014 3
2015 5
2016 20
2017 8
2018 9
2019 9
2020 4
2021 9
2022 10
2023 9
2024 15
2025 12
Total 136
Download as CSV

Ming-Song Chen publication distribution in Materials Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Materials Science in 2026. The highlighted bar marks where Ming-Song Chen sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 57 bars. Horizontal axis: publications, 50–69 to 1,163+. Vertical axis: number of scientists, 0 to 891. Most scientists, 891, have 190–209 publications. The last bar groups every scientist with 1,163 publications or more. The highlighted bar, 90–109 publications, is where this scientist sits. 50–69 publications: 28 scientists 70–89 publications: 152 scientists 90–109 publications: 356 scientists 110–129 publications: 487 scientists 130–149 publications: 723 scientists 150–169 publications: 835 scientists 170–189 publications: 850 scientists 190–209 publications: 891 scientists 210–229 publications: 862 scientists 230–249 publications: 766 scientists 250–269 publications: 726 scientists 270–289 publications: 665 scientists 290–309 publications: 593 scientists 310–329 publications: 537 scientists 330–349 publications: 477 scientists 350–369 publications: 440 scientists 370–389 publications: 356 scientists 390–409 publications: 321 scientists 410–429 publications: 256 scientists 430–449 publications: 246 scientists 450–469 publications: 216 scientists 470–489 publications: 212 scientists 490–509 publications: 174 scientists 510–529 publications: 194 scientists 530–549 publications: 162 scientists 550–569 publications: 131 scientists 570–589 publications: 111 scientists 590–609 publications: 103 scientists 610–629 publications: 99 scientists 630–649 publications: 77 scientists 650–669 publications: 92 scientists 670–689 publications: 56 scientists 690–709 publications: 53 scientists 710–729 publications: 53 scientists 730–749 publications: 38 scientists 750–769 publications: 52 scientists 770–789 publications: 43 scientists 790–809 publications: 38 scientists 810–829 publications: 34 scientists 830–849 publications: 25 scientists 850–869 publications: 18 scientists 870–889 publications: 20 scientists 890–909 publications: 24 scientists 910–929 publications: 27 scientists 930–949 publications: 20 scientists 950–969 publications: 17 scientists 970–989 publications: 10 scientists 990–1,009 publications: 16 scientists 1,010–1,029 publications: 13 scientists 1,030–1,049 publications: 12 scientists 1,050–1,069 publications: 9 scientists 1,070–1,089 publications: 8 scientists 1,090–1,109 publications: 7 scientists 1,110–1,129 publications: 9 scientists 1,130–1,149 publications: 2 scientists 1,150–1,162 publications: 5 scientists 1,163+ publications: 100 scientists
50–69 publications 1,163+

This scientist: 101 publications — 3rd percentile

3% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,163 publications or more.

View publications distribution as a table
Number of Materials Science scientists by publication count, Research.com 2026 ranking edition. Based on 12,847 ranked scientists.
Publications Scientists This scientist
50–69 28
70–89 152
90–109 356 101
110–129 487
130–149 723
150–169 835
170–189 850
190–209 891
210–229 862
230–249 766
250–269 726
270–289 665
290–309 593
310–329 537
330–349 477
350–369 440
370–389 356
390–409 321
410–429 256
430–449 246
450–469 216
470–489 212
490–509 174
510–529 194
530–549 162
550–569 131
570–589 111
590–609 103
610–629 99
630–649 77
650–669 92
670–689 56
690–709 53
710–729 53
730–749 38
750–769 52
770–789 43
790–809 38
810–829 34
830–849 25
850–869 18
870–889 20
890–909 24
910–929 27
930–949 20
950–969 17
970–989 10
990–1,009 16
1,010–1,029 13
1,030–1,049 12
1,050–1,069 9
1,070–1,089 8
1,090–1,109 7
1,110–1,129 9
1,130–1,149 2
1,150–1,162 5
1,163+ 100
Download as CSV

Ming-Song Chen D-index placement in Materials Science in 2026

The chart shows the D-index (discipline H-index) distribution of Materials Science scientists ranked by Research.com in 2026. The highlighted bar marks where Ming-Song Chen sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 64 bars. Horizontal axis: D-Index, 40–41 to 165+. Vertical axis: number of scientists, 0 to 667. Most scientists, 667, have 52–53 D-Index. The last bar groups every scientist with 165 D-Index or more. The highlighted bar, 50–51 D-Index, is where this scientist sits. 40–41 D-Index: 211 scientists 42–43 D-Index: 450 scientists 44–45 D-Index: 612 scientists 46–47 D-Index: 612 scientists 48–49 D-Index: 598 scientists 50–51 D-Index: 657 scientists 52–53 D-Index: 667 scientists 54–55 D-Index: 621 scientists 56–57 D-Index: 597 scientists 58–59 D-Index: 610 scientists 60–61 D-Index: 587 scientists 62–63 D-Index: 606 scientists 64–65 D-Index: 533 scientists 66–67 D-Index: 490 scientists 68–69 D-Index: 469 scientists 70–71 D-Index: 378 scientists 72–73 D-Index: 421 scientists 74–75 D-Index: 359 scientists 76–77 D-Index: 323 scientists 78–79 D-Index: 299 scientists 80–81 D-Index: 230 scientists 82–83 D-Index: 210 scientists 84–85 D-Index: 195 scientists 86–87 D-Index: 203 scientists 88–89 D-Index: 175 scientists 90–91 D-Index: 175 scientists 92–93 D-Index: 142 scientists 94–95 D-Index: 121 scientists 96–97 D-Index: 117 scientists 98–99 D-Index: 107 scientists 100–101 D-Index: 88 scientists 102–103 D-Index: 85 scientists 104–105 D-Index: 68 scientists 106–107 D-Index: 62 scientists 108–109 D-Index: 57 scientists 110–111 D-Index: 45 scientists 112–113 D-Index: 49 scientists 114–115 D-Index: 50 scientists 116–117 D-Index: 34 scientists 118–119 D-Index: 38 scientists 120–121 D-Index: 37 scientists 122–123 D-Index: 29 scientists 124–125 D-Index: 28 scientists 126–127 D-Index: 24 scientists 128–129 D-Index: 33 scientists 130–131 D-Index: 28 scientists 132–133 D-Index: 21 scientists 134–135 D-Index: 20 scientists 136–137 D-Index: 23 scientists 138–139 D-Index: 17 scientists 140–141 D-Index: 12 scientists 142–143 D-Index: 17 scientists 144–145 D-Index: 21 scientists 146–147 D-Index: 13 scientists 148–149 D-Index: 11 scientists 150–151 D-Index: 14 scientists 152–153 D-Index: 13 scientists 154–155 D-Index: 9 scientists 156–157 D-Index: 10 scientists 158–159 D-Index: 7 scientists 160–161 D-Index: 4 scientists 162–163 D-Index: 4 scientists 164 D-Index: 3 scientists 165+ D-Index: 98 scientists
40–41 D-Index 165+

This scientist: 50 D-Index — 22nd percentile

22% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 165 D-Index or more.

View D-Index distribution as a table
Number of Materials Science scientists by D-index, Research.com 2026 ranking edition. Based on 12,847 ranked scientists.
D-Index Scientists This scientist
40–41 211
42–43 450
44–45 612
46–47 612
48–49 598
50–51 657 50
52–53 667
54–55 621
56–57 597
58–59 610
60–61 587
62–63 606
64–65 533
66–67 490
68–69 469
70–71 378
72–73 421
74–75 359
76–77 323
78–79 299
80–81 230
82–83 210
84–85 195
86–87 203
88–89 175
90–91 175
92–93 142
94–95 121
96–97 117
98–99 107
100–101 88
102–103 85
104–105 68
106–107 62
108–109 57
110–111 45
112–113 49
114–115 50
116–117 34
118–119 38
120–121 37
122–123 29
124–125 28
126–127 24
128–129 33
130–131 28
132–133 21
134–135 20
136–137 23
138–139 17
140–141 12
142–143 17
144–145 21
146–147 13
148–149 11
150–151 14
152–153 13
154–155 9
156–157 10
158–159 7
160–161 4
162–163 4
164 3
165+ 98
Download as CSV

Overview

Ming-Song Chen is affiliated with Central South University in China and has a research focus primarily in Computer Science and Engineering. Their work spans several key subfields, including Artificial Intelligence, Computer Networks and Communications, Computer Vision and Pattern Recognition, Information Systems, and Electrical and Electronic Engineering.

The scientist's research explores a range of topics, notably:

  • Privacy-Preserving Technologies in Data
  • Internet Traffic Analysis and Secure E-voting
  • Cloud Computing and Resource Management
  • Advanced Neural Network Applications
  • IoT and Edge/Fog Computing
  • Adversarial Robustness in Machine Learning
  • Anomaly Detection Techniques and Applications

Chen has published significantly in journals and conference venues such as arXiv (Cornell University), IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Journal of Systems Architecture, Journal of Circuits Systems and Computers, and IEEE Transactions on Computers. The highest number of publications appear in arXiv with 48 contributions, followed by 13 papers in IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

Their notable recent papers include:

  • Developing a stable high-performance soybean meal-based adhesive using a simple high-pressure homogenization technology (2020), Journal of Cleaner Production
  • Efficient Federated Learning for Cloud-Based AIoT Applications (2020), IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • FDA³: Federated Defense Against Adversarial Attacks for Cloud-Based IIoT Applications (2020), IEEE Transactions on Industrial Informatics
  • Throughput-Conscious Energy Allocation and Reliability-Aware Task Assignment for Renewable Powered In-Situ Server Systems (2021), IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
  • A High-Performance Bio-Adhesive Using Hyperbranched Aminated Soybean Polysaccharide and Bio-Based Epoxide (2020), Advanced Materials Interfaces

Ming-Song Chen frequently collaborates with co-authors including Xian Wei, Ting Wang, Tongquan Wei, Ming Hu, and Junlong Zhou.

In addition to research papers, Chen has authored a book titled Machine Learning Empowered Intelligent Data Center Networking published by Springer Nature in 2023.

Best Publications

  • Constitutive modeling for elevated temperature flow behavior of 42CrMo steel

    Y.C. Lin;Ming-Song Chen;Jue Zhong

  • Prediction of 42CrMo steel flow stress at high temperature and strain rate

    Y.C. Lin;Ming-Song Chen;Jue Zhong

  • Constitutive descriptions for hot compressed 2124-T851 aluminum alloy over a wide range of temperature and strain rate

    Y.C. Lin;Yu-Chi Xia;Xiao-Min Chen;Ming-Song Chen

  • EBSD analysis of evolution of dynamic recrystallization grains and δ phase in a nickel-based superalloy during hot compressive deformation

    Y.C. Lin;Dao-Guang He;Ming-Song Chen;Xiao-Min Chen

  • A physically-based constitutive model for a typical nickel-based superalloy

    Y.C. Lin;Xiao-Min Chen;Dong-Xu Wen;Ming-Song Chen

  • Effect of temperature and strain rate on the compressive deformation behavior of 42CrMo steel

    Y.C. Lin;Ming-Song Chen;Jue Zhong

  • Modeling of flow stress of 42CrMo steel under hot compression

    Yong-Cheng Lin;Ming-Song Chen;Jun Zhang

  • The kinetics of dynamic recrystallization of 42CrMo steel

    Ming-Song Chen;Y.C. Lin;Xue-Song Ma

  • Microstructural evolution of a nickel-based superalloy during hot deformation

    Xiao-Min Chen;Y.C. Lin;Ming-Song Chen;Hong-Bin Li

  • Study of dynamic recrystallization in a Ni-based superalloy by experiments and cellular automaton model

    Yan-Xing Liu;Y.C. Lin;Hong-Bin Li;Dong-Xu Wen

  • Microstructural evolution and constitutive models to predict hot deformation behaviors of a nickel-based superalloy

    Y.C. Lin;Fu-Qi Nong;Xiao-Min Chen;Dong-Dong Chen

  • Study of static recrystallization kinetics in a low alloy steel

    Y.C. Lin;Ming-Song Chen;Jue Zhong

  • Microstructural evolution in 42CrMo steel during compression at elevated temperatures

    Y.C. Lin;Ming-Song Chen;Jue Zhong

  • Microstructural evolution and support vector regression model for an aged Ni-based superalloy during two-stage hot forming with stepped strain rates

    Dao-Guang He;Y.C. Lin;Jian Chen;Dong-Dong Chen

  • Numerical simulation for stress/strain distribution and microstructural evolution in 42CrMo steel during hot upsetting process

    Y.C. Lin;Ming-Song Chen;Jue Zhong

  • Effects of initial microstructures on hot tensile deformation behaviors and fracture characteristics of Ti-6Al-4V alloy

    Y.C. Lin;Xing-You Jiang;Ci-jun Shuai;Chun-Yang Zhao

  • Study of metadynamic recrystallization behaviors in a low alloy steel

    Y.C. Lin;Ming-Song Chen;Jue Zhong

  • Study of static recrystallization behavior in hot deformed Ni-based superalloy using cellular automaton model

    Y.C. Lin;Yan-Xing Liu;Ming-Song Chen;Ming-Hui Huang

  • Effects of deformation temperatures on stress/strain distribution and microstructural evolution of deformed 42CrMo steel

    Y.C. Lin;Ming-Song Chen;Jue Zhong

  • Modeling and simulation of dynamic recrystallization behavior for 42CrMo steel by an extended cellular automaton method

    Ming-Song Chen;Wu-Quan Yuan;Y.C. Lin;Hong-Bin Li

  • Dislocation substructures evolution and an adaptive-network-based fuzzy inference system model for constitutive behavior of a Ni-based superalloy during hot deformation

    Dong-Dong Chen;Y.C. Lin;Ying Zhou;Ming-Song Chen

Frequent Co-Authors

Y.C. Lin
Y.C. Lin Central South University
Cijun Shuai
Cijun Shuai Central South University

External Links

Google Scholar page

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Best Scientists Citing Ming-Song Chen

Y.C. Lin

Y.C. Lin

Central South University

Publications: 93

Hamed Mirzadeh

Hamed Mirzadeh

University of Tehran

Publications: 37

Sumantra Mandal

Sumantra Mandal

Indian Institute of Technology Kharagpur

Publications: 32

Shun-Peng Zhu

Shun-Peng Zhu

University of Electronic Science and Technology of China

Publications: 30

A.K. Bhaduri

A.K. Bhaduri

Indira Gandhi Centre for Atomic Research

Publications: 22

Guoqun Zhao

Guoqun Zhao

Shandong University

Publications: 20

Jie Zhou

Jie Zhou

Delft University of Technology

Publications: 19

Jianjun Li

Jianjun Li

Chinese Academy of Sciences

Publications: 16

Mw W. Fu

Mw W. Fu

Hong Kong Polytechnic University

Publications: 13

Jinshan Li

Jinshan Li

Northwestern Polytechnical University

Publications: 13

Yongchang Liu

Yongchang Liu

Tianjin University

Publications: 12

Jianguo Lin

Jianguo Lin

Hong Kong Polytechnic University

Publications: 11

Chi Zhang

Chi Zhang

Hohai University

Publications: 11

Zhengyi Jiang

Zhengyi Jiang

University of Wollongong

Publications: 11

Hailong Zhang

Hailong Zhang

University of Science and Technology Beijing

Publications: 10

Lin Hua

Lin Hua

Wuhan University of Technology

Publications: 10

Trending Scientists

Ming-Bo Yang

Ming-Bo Yang

Sichuan University

Hans Ellegren

Hans Ellegren

Uppsala University

James P. McCullough

James P. McCullough

Virginia Commonwealth University

Yhu Chering Huang

Yhu Chering Huang

Chang Gung Memorial Hospital

Anja G. Teschemacher

Anja G. Teschemacher

University of Bristol

Mark P. Mattson

Mark P. Mattson

Johns Hopkins University

Alain Dagher

Alain Dagher

Montreal Neurological Institute and Hospital

Jadran Faganeli

Jadran Faganeli

University of Ljubljana

Kiyoshi Yasukawa

Kiyoshi Yasukawa

Kyoto University

Benjamin L. Turner

Benjamin L. Turner

Gyeongsang National University

Leonard J. Foster

Leonard J. Foster

University of British Columbia

Jorien E. Vonk

Jorien E. Vonk

Vrije Universiteit Amsterdam

Marcelo H. Ang

Marcelo H. Ang

National University of Singapore

Chuanyong Jing

Chuanyong Jing

Chinese Academy of Sciences

Assaf Razin

Assaf Razin

Tel Aviv University

Joshua J. Lawler

Joshua J. Lawler

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