World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
66
Citations
25389
World Ranking
2269
National Ranking
1134

Sun-Yuan Kung publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Sun-Yuan Kung sits on this spectrum.

32–41 publications: 7 scientists 42–51 publications: 22 scientists 52–61 publications: 82 scientists 62–71 publications: 134 scientists 72–81 publications: 249 scientists 82–91 publications: 324 scientists 92–101 publications: 421 scientists 102–111 publications: 420 scientists 112–121 publications: 497 scientists 122–131 publications: 544 scientists 132–141 publications: 555 scientists 142–151 publications: 609 scientists 152–161 publications: 559 scientists 162–171 publications: 534 scientists 172–181 publications: 556 scientists 182–191 publications: 583 scientists 192–201 publications: 519 scientists 202–211 publications: 508 scientists 212–221 publications: 490 scientists 222–231 publications: 437 scientists 232–241 publications: 423 scientists 242–251 publications: 408 scientists 252–261 publications: 377 scientists 262–271 publications: 301 scientists 272–281 publications: 335 scientists 282–291 publications: 320 scientists 292–301 publications: 293 scientists 302–311 publications: 250 scientists 312–321 publications: 238 scientists 322–331 publications: 206 scientists 332–341 publications: 209 scientists 342–351 publications: 208 scientists 352–361 publications: 162 scientists 362–371 publications: 176 scientists 372–381 publications: 127 scientists 382–391 publications: 158 scientists 392–401 publications: 128 scientists 402–411 publications: 104 scientists 412–421 publications: 94 scientists 422–431 publications: 99 scientists 432–441 publications: 83 scientists 442–451 publications: 108 scientists 452–461 publications: 73 scientists 462–471 publications: 77 scientists 472–481 publications: 69 scientists 482–491 publications: 84 scientists 492–501 publications: 62 scientists 502–511 publications: 54 scientists 512–521 publications: 57 scientists 522–531 publications: 51 scientists 532–541 publications: 51 scientists 542–551 publications: 32 scientists 552–561 publications: 38 scientists 562–571 publications: 28 scientists 572–581 publications: 43 scientists 582–591 publications: 33 scientists 592–601 publications: 41 scientists 602–611 publications: 32 scientists 612–621 publications: 28 scientists 622–631 publications: 25 scientists 632–641 publications: 27 scientists 642–651 publications: 17 scientists 652–661 publications: 20 scientists 662–671 publications: 17 scientists 672–681 publications: 15 scientists 682–691 publications: 14 scientists 692–701 publications: 21 scientists 702–711 publications: 13 scientists 712–721 publications: 12 scientists 722–731 publications: 19 scientists 732–741 publications: 14 scientists 742–751 publications: 12 scientists 752–761 publications: 10 scientists 762–771 publications: 10 scientists 772–781 publications: 11 scientists 782–791 publications: 10 scientists 792–801 publications: 11 scientists 802–811 publications: 8 scientists 812–821 publications: 8 scientists 822–831 publications: 7 scientists 832–841 publications: 11 scientists 842–851 publications: 10 scientists 852–861 publications: 5 scientists 862–871 publications: 9 scientists 872–881 publications: 4 scientists 882–891 publications: 6 scientists 892–901 publications: 3 scientists 902–911 publications: 6 scientists 912–921 publications: 3 scientists 922–931 publications: 2 scientists 932–941 publications: 2 scientists 942–951 publications: 2 scientists 952–961 publications: 3 scientists 962–971 publications: 3 scientists 972–981 publications: 3 scientists 982–990 publications: 5 scientists 991+ publications: 100 scientists
32 publications 991+

This scientist: 474 publications — 92nd percentile

92% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Sun-Yuan Kung D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Sun-Yuan Kung sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 983 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 968 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 763 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 518 scientists 54–55 D-Index: 500 scientists 56–57 D-Index: 458 scientists 58–59 D-Index: 400 scientists 60–61 D-Index: 337 scientists 62–63 D-Index: 308 scientists 64–65 D-Index: 292 scientists 66–67 D-Index: 249 scientists 68–69 D-Index: 213 scientists 70–71 D-Index: 192 scientists 72–73 D-Index: 189 scientists 74–75 D-Index: 165 scientists 76–77 D-Index: 139 scientists 78–79 D-Index: 119 scientists 80–81 D-Index: 121 scientists 82–83 D-Index: 113 scientists 84–85 D-Index: 88 scientists 86–87 D-Index: 87 scientists 88–89 D-Index: 75 scientists 90–91 D-Index: 69 scientists 92–93 D-Index: 57 scientists 94–95 D-Index: 46 scientists 96–97 D-Index: 38 scientists 98–99 D-Index: 34 scientists 100–101 D-Index: 36 scientists 102–103 D-Index: 27 scientists 104–105 D-Index: 37 scientists 106–107 D-Index: 18 scientists 108–109 D-Index: 31 scientists 110–111 D-Index: 19 scientists 112–113 D-Index: 16 scientists 114–115 D-Index: 12 scientists 116–117 D-Index: 20 scientists 118–119 D-Index: 15 scientists 120–121 D-Index: 5 scientists 122–123 D-Index: 20 scientists 124–125 D-Index: 8 scientists 126–127 D-Index: 5 scientists 128–129 D-Index: 7 scientists 130 D-Index: 3 scientists 131+ D-Index: 98 scientists
30 D-Index 131+

This scientist: 66 D-Index — 84th percentile

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

The last bar groups every scientist with 131 D-Index or more.

Research.com Recognitions

  • 1988 - IEEE Fellow For contributions to very-large-scale-integrated arrays for signal processing.

Overview

Sun-Yuan Kung is affiliated with Princeton University in the United States. Their research primarily spans the field of Computer Science, with a particular focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Radiology, Nuclear Medicine and Imaging, and Biomedical Engineering.

The scientist's work covers multiple topics, including:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Anomaly Detection Techniques and Applications
  • Advanced Image Processing Techniques
  • Advanced Vision and Imaging
  • Adversarial Robustness in Machine Learning
  • Multimodal Machine Learning Applications

Some of the recent papers authored by or involving Sun-Yuan Kung include:

  • CHEX: CHannel EXploration for CNN Model Compression, 2022, published at the 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • A Novel Multi-Stage Training Approach for Human Activity Recognition From Multimodal Wearable Sensor Data Using Deep Neural Network, 2020, IEEE Sensors Journal
  • Adversarial Learning for Multiscale Crowd Counting Under Complex Scenes, 2020, IEEE Transactions on Cybernetics
  • Intelligent security and optimization in Edge/Fog Computing, 2020, Future Generation Computer Systems
  • Exploiting Operation Importance for Differentiable Neural Architecture Search, 2021, IEEE Transactions on Neural Networks and Learning Systems

The scientist frequently collaborates with the following co-authors:

  • Yuan Zhou
  • Zejiang Hou
  • Shuwei Huo
  • Shaikh Anowarul Fattah
  • Yogendra Rao Musunuri

Publication venues where Sun-Yuan Kung's work is commonly featured include:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • IEEE Transactions on Neural Networks and Learning Systems
  • IEEE Transactions on Geoscience and Remote Sensing
  • IEEE Transactions on Multimedia

In 1988, Sun-Yuan Kung was awarded the IEEE Fellow title for contributions to very-large-scale-integrated arrays for signal processing.

Best Publications

  • VLSI Array processors

    S. Kung

  • Optical interconnections for VLSI systems

    J.W. Goodman;F.J. Leonberger;Sun-Yuan Kung;R.A. Athale

  • Principal Component Neural Networks: Theory and Applications

    K. I. Diamantaras;S. Y. Kung

  • Face recognition/detection by probabilistic decision-based neural network

    Shang-Hung Lin;Sun-Yuan Kung;Long-Ji Lin

  • Information Exchange in Wireless Networks with Network Coding and Physical-layer Broadcast

    Yunnan Wu;Philip A. Chou;Sun-Yuan Kung

  • Digital Neural Networks

    S. Y. Kung

  • A new identification and model reduction algorithm via singular value decomposition

    S. Y. Kung

  • Variable-phase-shift-based RF-baseband codesign for MIMO antenna selection

    Xinying Zhang;A.F. Molisch;Sun-Yuan Kung

  • State-space and singular-value decomposition-based approximation methods for the harmonic retrieval problem

    S. Y. Kung;K. S. Arun;D. V. Bhaskar Rao

  • On supercomputing with systolic/wavefront array processors

    Sun-Yuan Kung

  • Minimum-energy multicast in mobile ad hoc networks using network coding

    Yunnan Wu;P.A. Chou;Sun-Yuan Kung

  • Optimal Hankel-norm model reductions: Multivariable systems

    Sun-yuan Kung;David Lin

  • Wavefront Array Processor: Language, Architecture, and Applications

    Sun-Yuan Kung;Arun;Gal-Ezer;Bhaskar Rao

  • Network planning in wireless ad hoc networks: a cross-Layer approach

    Y. Wu;P.A. Chou;Qian Zhang;K. Jain

  • Neural network for locating and recognizing a deformable object

    Sun-Yuan Kung;Shang-Hung Lin;Long-Ji Lin;Ming Fang

  • Adaptive notch filtering for the retrieval of sinusoids in noise

    D.B. Rao;Sun-Yuan Kung

  • VLSI and Modern Signal Processing

    S. Y. Kung;Thomas Kailath;Harper J. Whitehouse

  • Kernel Methods and Machine Learning

    S. Y. Kung

  • Biometric Authentication: A Machine Learning Approach

    S. Y. Kung;M. W. Mak;S. H. Lin

  • A neural network learning algorithm for adaptive principal component extraction (APEX)

    S.Y. Kung;K.I. Diamantaras

  • Greatest common divisor via generalized Sylvester and Bezout matrices

    R. Bitmead;S.-Y. Kung;B. Anderson;T. Kailath

  • New results in 2-D systems theory, part I: 2-D polynomial matrices, factorization, and coprimeness

    M. Morf;B.C. Levy;Sun-Yuan Kung

Frequent Co-Authors

Man-Wai Mak
Man-Wai Mak Hong Kong Polytechnic University
Jenq-Neng Hwang
Jenq-Neng Hwang University of Washington
Thomas Kailath
Thomas Kailath Stanford University
Yue Wang
Yue Wang Zhejiang University
Anthony Vetro
Anthony Vetro Mitsubishi Electric (United States)
Yu Hen Hu
Yu Hen Hu University of Wisconsin–Madison
Huifang Sun
Huifang Sun Mitsubishi Electric (United States)
Yen-Kuang Chen
Yen-Kuang Chen Alibaba Group (China)
Ling Guan
Ling Guan Toronto Metropolitan University
Chad L. Myers
Chad L. Myers University of Minnesota

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science opens up many flexible educational and career options. For those looking to start their journey, associates degrees online offer a quick entry point into the tech field—ideal for building foundational skills or pivoting careers.

Affordability is a key consideration for most students. With a growing number of affordable online courses, you can access quality Computer Science programs that fit a range of budgets. This flexibility makes higher education more accessible than ever.

Admission requirements can be a challenge, especially for those with non-traditional academic backgrounds. Fortunately, there are options—many reputable college with low gpa programs provide pathways for motivated learners, regardless of past grades.

Thinking beyond Computer Science, interdisciplinary learning is also valuable. For instance, if you’re interested in technology’s impact on the planet, consider, what can you do with an environmental science major—these fields increasingly overlap in areas like data analysis and sustainability.

Best Scientists Citing Sun-Yuan Kung

Trending Scientists

Recently Published Articles