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Yu-Dong Yao

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Electronics and Electrical Engineering 52 2522 2418 965 903 251 10560
Computer Science 61 3104 3013 1513 1456 300 13467

Yu-Dong Yao publications per year

The chart shows the history of publications by Yu-Dong Yao between 1986 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Yu-Dong Yao published across 41 years, from 1986 to 2026, averaging 12.5 papers a year. Output peaked at 61 publications in 2023. 42 of the 514 publications appeared in the last two years.

No. of publications
20 40 60
Bar chart. Horizontal axis: year, 1986 to 2026. Vertical axis: number of publications, 0 to 61. Peak 61 publications in 2023. 1986: 1 publication 1987: 0 publications 1988: 2 publications 1989: 1 publication 1990: 2 publications 1991: 0 publications 1992: 4 publications 1993: 2 publications 1994: 2 publications 1995: 2 publications 1996: 1 publication 1997: 11 publications 1998: 0 publications 1999: 1 publication 2000: 4 publications 2001: 14 publications 2002: 10 publications 2003: 8 publications 2004: 13 publications 2005: 9 publications 2006: 9 publications 2007: 6 publications 2008: 6 publications 2009: 8 publications 2010: 15 publications 2011: 11 publications 2012: 13 publications 2013: 4 publications 2014: 12 publications 2015: 7 publications 2016: 9 publications 2017: 9 publications 2018: 12 publications 2019: 22 publications 2020: 34 publications 2021: 47 publications 2022: 55 publications 2023: 61 publications 2024: 45 publications 2025: 41 publications 2026: 1 publication
1986 2026

514 publications in total across all disciplines

View publications per year as a table
Yu-Dong Yao: publications per year, 1986 to 2026
Year Publications
1986 1
1987 0
1988 2
1989 1
1990 2
1991 0
1992 4
1993 2
1994 2
1995 2
1996 1
1997 11
1998 0
1999 1
2000 4
2001 14
2002 10
2003 8
2004 13
2005 9
2006 9
2007 6
2008 6
2009 8
2010 15
2011 11
2012 13
2013 4
2014 12
2015 7
2016 9
2017 9
2018 12
2019 22
2020 34
2021 47
2022 55
2023 61
2024 45
2025 41
2026 1
Total 514
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Yu-Dong Yao publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Yu-Dong Yao sits on this spectrum.

No. of scientists
100 200 300 400
Bar chart with 53 bars. Horizontal axis: publications, 34–53 to 1,065+. Vertical axis: number of scientists, 0 to 445. Most scientists, 445, have 174–193 publications. The last bar groups every scientist with 1,065 publications or more. The highlighted bar, 234–253 publications, is where this scientist sits. 34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34–53 publications 1,065+

This scientist: 251 publications — 45th percentile

45% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

View publications distribution as a table
Number of Electronics and Electrical Engineering scientists by publication count, Research.com 2026 ranking edition. Based on 6,875 ranked scientists.
Publications Scientists This scientist
34–53 24
54–73 52
74–93 114
94–113 203
114–133 269
134–153 355
154–173 403
174–193 445
194–213 430
214–233 431
234–253 399 251
254–273 366
274–293 335
294–313 300
314–333 276
334–353 250
354–373 214
374–393 187
394–413 152
414–433 169
434–453 147
454–473 111
474–493 117
494–513 103
514–533 99
534–553 92
554–573 75
574–593 58
594–613 69
614–633 50
634–653 62
654–673 54
674–693 44
694–713 37
714–733 28
734–753 26
754–773 26
774–793 19
794–813 23
814–833 20
834–853 16
854–873 20
874–893 11
894–913 11
914–933 16
934–953 13
954–973 10
974–993 11
994–1,013 9
1,014–1,033 9
1,034–1,053 10
1,054–1,064 6
1,065+ 99
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Yu-Dong Yao D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Yu-Dong Yao sits on this spectrum.

No. of scientists
50 100 150 200 250
Bar chart with 82 bars. Horizontal axis: D-Index, 30 to 111+. Vertical axis: number of scientists, 0 to 263. Most scientists, 263, have 32 D-Index. The last bar groups every scientist with 111 D-Index or more. The highlighted bar, 52 D-Index, is where this scientist sits. 30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 52 D-Index — 64th percentile

64% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

View D-Index distribution as a table
Number of Electronics and Electrical Engineering scientists by D-index, Research.com 2026 ranking edition. Based on 6,875 ranked scientists.
D-Index Scientists This scientist
30 178
31 257
32 263
33 262
34 244
35 236
36 211
37 220
38 214
39 214
40 205
41 187
42 194
43 201
44 155
45 189
46 148
47 160
48 134
49 130
50 141
51 156
52 108 52
53 130
54 112
55 97
56 111
57 102
58 108
59 120
60 103
61 93
62 92
63 74
64 77
65 73
66 64
67 69
68 60
69 39
70 57
71 59
72 46
73 49
74 38
75 35
76 32
77 35
78 31
79 22
80 34
81 31
82 34
83 23
84 18
85 30
86 19
87 19
88 20
89 8
90 17
91 7
92 14
93 9
94 15
95 10
96 12
97 10
98 10
99 12
100 16
101 5
102 7
103 7
104 8
105 9
106 13
107 4
108 5
109 10
110 8
111+ 96
Download as CSV

Overview

Yu-Dong Yao is affiliated with the Stevens Institute of Technology in the United States. Their scientific work spans multiple disciplines with a focus on Medicine, Engineering, and Computer Science. Within these broad fields, their research delves into several subfields including Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, and Electrical and Electronic Engineering.

The primary topics of Yu-Dong Yao's research encompass Radiomics and Machine Learning in Medical Imaging, AI applications in cancer detection, COVID-19 diagnosis using AI, Cell Image Analysis Techniques, Medical Imaging Techniques and Applications, Lung Cancer Diagnosis and Treatment, and Digital Imaging for Blood Diseases.

Their recent papers include:

  • Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches, 2020, Journal of X-Ray Science and Technology
  • DeepCervix: A deep learning-based framework for the classification of cervical cells using hybrid deep feature fusion techniques, 2021, Computers in Biology and Medicine
  • A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches, 2022, Artificial Intelligence Review
  • A Survey of Modulation Classification Using Deep Learning: Signal Representation and Data Preprocessing, 2021, IEEE Transactions on Neural Networks and Learning Systems
  • A review of deep learning-based multiple-lesion recognition from medical images: classification, detection and segmentation, 2023, Computers in Biology and Medicine

Yu-Dong Yao frequently publishes in venues such as arXiv (Cornell University), IEEE Access, Computers in Biology and Medicine, Physics in Medicine and Biology, and IEEE Journal of Biomedical and Health Informatics. These venues represent a range of platforms addressing both the technical and medical aspects of their research.

Collaboration is a significant component of their research, working often with coauthors including Chen Li, Shouliang Qi, Yueyang Teng, Md Mamunur Rahaman, and Marcin Grzegorzek. The frequency of these collaborations indicates ongoing partnerships in their research efforts.

Best Publications

  • Modulation Classification Based on Signal Constellation Diagrams and Deep Learning

    Shengliang Peng;Hanyu Jiang;Huaxia Wang;Hathal Alwageed

  • An Adaptive Cooperation Diversity Scheme With Best-Relay Selection in Cognitive Radio Networks

    Yulong Zou;Jia Zhu;Baoyu Zheng;Yu-Dong Yao

  • An Amateur Drone Surveillance System Based on the Cognitive Internet of Things

    Guoru Ding;Qihui Wu;Linyuan Zhang;Yun Lin

  • Deterministic multiuser carrier-frequency offset estimation for interleaved OFDMA uplink

    Zhongren Cao;U. Tureli;Yu-Dong Yao

  • Opportunistic Spectrum Access in Cognitive Radio Networks: Global Optimization Using Local Interaction Games

    Yuhua Xu;Jinlong Wang;Qihui Wu;A. Anpalagan

  • Breast Cancer Detection Using Extreme Learning Machine Based on Feature Fusion With CNN Deep Features

    Zhiqiong Wang;Mo Li;Huaxia Wang;Hanyu Jiang

  • Opportunistic Spectrum Access in Unknown Dynamic Environment: A Game-Theoretic Stochastic Learning Solution

    Yuhua Xu;Jinlong Wang;Qihui Wu;A. Anpalagan

  • Identification of COVID-19 samples from chest X-Ray images using deep learning: A comparison of transfer learning approaches.

    Mamunur Rahaman;Chen Li;Yudong Yao;Frank Kulwa

  • Investigations into cochannel interference in microcellular mobile radio systems

    Y.-D. Yao;A.U.H. Sheikh

  • DeepCervix: A deep learning-based framework for the classification of cervical cells using hybrid deep feature fusion techniques.

    Mamunur Rahaman;Chen Li;Yudong Yao;Frank Kulwa

  • Spatial-Temporal Opportunity Detection for Spectrum-Heterogeneous Cognitive Radio Networks: Two-Dimensional Sensing

    Qihui Wu;Guoru Ding;Jinlong Wang;Yu-Dong Yao

  • Outage probability analysis for microcell mobile radio systems with cochannel interferers in Rician/Rayleigh fading environment

    Y.-D. Yao;A.U.H. Sheikh

  • A Comprehensive Review of Computer-aided Whole-slide Image Analysis: from Datasets to Feature Extraction, Segmentation, Classification, and Detection Approaches.

    Chen Li;Xintong Li;Mamunur Rahaman;Xiaoyan Li

  • A Survey of Modulation Classification Using Deep Learning: Signal Representation and Data Preprocessing

    Shengliang Peng;Shujun Sun;Yu-Dong Yao

  • Cooperative relay techniques for cognitive radio systems: Spectrum sensing and secondary user transmissions

    Yulong Zou;Yu-Dong Yao;Baoyu Zheng

  • Kernel-Based Learning for Statistical Signal Processing in Cognitive Radio Networks: Theoretical Foundations, Example Applications, and Future Directions

    Guoru Ding;Qihui Wu;Yu-Dong Yao;Jinlong Wang

  • Cellular-Base-Station-Assisted Device-to-Device Communications in TV White Space

    Guoru Ding;Jinlong Wang;Qihui Wu;Yu-Dong Yao

  • Method and apparatus of preserving power of a remote unit in a dispatch system

    Eric J. Lekven;Yu-Dong Yao;Matthew S. Grob

  • Modulation classification using convolutional Neural Network based deep learning model

    Shengliang Peng;Hanyu Jiang;Huaxia Wang;Hathal Alwageed

  • A Comprehensive Review for Breast Histopathology Image Analysis Using Classical and Deep Neural Networks

    Xiaomin Zhou;Chen Li;Mamunur Rahaman;Yudong Yao

  • Method and apparatus for efficient data transmission in a voice-over-data communication system

    Yu-Dong Yao

  • Securing physical-layer communications for cognitive radio networks

    Yulong Zou;Jia Zhu;Liuqing Yang;Ying-Chang Liang

  • Cooperative Spectrum Sensing in Cognitive Radio Networks in the Presence of the Primary User Emulation Attack

    Chao Chen;Hongbing Cheng;Yu-Dong Yao

  • Method and apparatus for access regulation and system protection of a dispatch system

    Matthew S. Grob;Yu-Dong Yao;Eric J. Lekven

  • An Amateur Drone Surveillance System Based on Cognitive Internet of Things

    Guoru Ding;Qihui Wu;Linyuan Zhang;Yun Lin

Frequent Co-Authors

Yulong Zou
Yulong Zou Nanjing University of Posts and Telecommunications
Qihui Wu
Qihui Wu Nanjing University of Aeronautics and Astronautics
Hongbin Li
Hongbin Li Stevens Institute of Technology
Guoru Ding
Guoru Ding Southeast University
Wei Qian
Wei Qian The University of Texas at El Paso
Yuhua Xu
Yuhua Xu Nanjing University of Posts and Telecommunications
Yingying Chen
Yingying Chen Rutgers, The State University of New Jersey
Theodoros A. Tsiftsis
Theodoros A. Tsiftsis University Of Thessaly
Haibo He
Haibo He University of Rhode Island
Zan Li
Zan Li Xidian University

External Links

Personal website of Yu-Dong Yao Google Scholar page

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Related Online Degrees & Career Pathways

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Additionally, a master's in training and development online prepares professionals to design effective technical training programs. This can be especially beneficial in engineering environments focused on workforce development and technology adoption.

Best Scientists Citing Yu-Dong Yao

Qihui Wu

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Publications: 90

Guoru Ding

Guoru Ding

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Publications: 77

Yuhua Xu

Yuhua Xu

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Publications: 73

Mohamed-Slim Alouini

Mohamed-Slim Alouini

King Abdullah University of Science and Technology

Publications: 61

Yulong Zou

Yulong Zou

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Publications: 55

Alagan Anpalagan

Alagan Anpalagan

Toronto Metropolitan University

Publications: 32

Khalid A. Qaraqe

Khalid A. Qaraqe

Hamad bin Khalifa University

Publications: 26

Lajos Hanzo

Lajos Hanzo

University of Southampton

Publications: 23

Mazen O. Hasna

Mazen O. Hasna

Qatar University

Publications: 22

Stephen G. Perlman

Stephen G. Perlman

Rearden

Publications: 21

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Publications: 18

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Georges Kaddoum

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Feifei Gao

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