World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
39
Citations
7008
World Ranking
9707
National Ranking
102

U Kang 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 U Kang 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: 164 publications — 32nd percentile

32% of scientists in this discipline score the same or lower.

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

U Kang 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 U Kang 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: 39 D-Index — 33rd percentile

33% of scientists in this discipline score the same or lower.

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

Overview

U Kang is affiliated with Seoul National University in South Korea and has contributed extensively to the field of computer science with a focus on artificial intelligence and related subfields. Their research output spans multiple specialized domains, including computer vision, information systems, and computational mathematics.

The main fields of study in U Kang's work include:

  • Computer Science

The scientist's subfields of study are:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Radiology, Nuclear Medicine and Imaging
  • Computational Mathematics

U Kang's research covers several prominent topics, notably:

  • Advanced Graph Neural Networks
  • Topic Modeling
  • Domain Adaptation and Few-Shot Learning
  • Recommender Systems and Techniques
  • Multimodal Machine Learning Applications
  • Tensor decomposition and applications
  • Graph Theory and Algorithms

The scientist has published papers in widely recognized venues, among which the most frequent include:

  • PLoS ONE
  • arXiv (Cornell University)
  • Knowledge and Information Systems
  • ACM Transactions on Knowledge Discovery from Data
  • 2022 IEEE International Conference on Big Data (Big Data)

Selected recent papers authored by U Kang include:

  • "Falcon: Lightweight and Accurate Convolution Based on Depthwise Separable Convolution," 2023, Knowledge and Information Systems
  • "Accurate Stock Movement Prediction with Self-supervised Learning from Sparse Noisy Tweets," 2022, 2022 IEEE International Conference on Big Data (Big Data)
  • "Model-Agnostic Augmentation for Accurate Graph Classification," 2022, Proceedings of the ACM Web Conference 2022
  • "Accurate Node Feature Estimation with Structured Variational Graph Autoencoder," 2022, Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
  • "Accurate Action Recommendation for Smart Home via Two-Level Encoders and Commonsense Knowledge," 2022, Proceedings of the 31st ACM International Conference on Information & Knowledge Management

Frequent collaborators with whom U Kang has coauthored multiple papers include:

  • Jun-Gi Jang
  • Hyunsik Jeon
  • Jaemin Yoo
  • Jinhong Jung
  • Sooyeon Shim

Best Publications

  • PEGASUS: A Peta-Scale Graph Mining System Implementation and Observations

    U. Kang;Charalampos E. Tsourakakis;Christos Faloutsos

  • DOULION: counting triangles in massive graphs with a coin

    Charalampos E. Tsourakakis;U. Kang;Gary L. Miller;Christos Faloutsos

  • GigaTensor: scaling tensor analysis up by 100 times - algorithms and discoveries

    U. Kang;Evangelos Papalexakis;Abhay Harpale;Christos Faloutsos

  • Clustering very large multi-dimensional datasets with MapReduce

    Robson Leonardo Ferreira Cordeiro;Caetano Traina;Agma Juci Machado Traina;Julio López

  • PEGASUS: mining peta-scale graphs

    U Kang;Charalampos E. Tsourakakis;Christos Faloutsos

  • Centralities in large networks: Algorithms and observations

    U. Kang;Spiros Papadimitriou;Jimeng Sun;Hanghang Tong

  • SlashBurn: Graph Compression and Mining beyond Caveman Communities

    Yongsub Lim;U Kang;Christos Faloutsos

  • Beyond 'Caveman Communities': Hubs and Spokes for Graph Compression and Mining

    U. Kang;Christos Faloutsos

  • HaTen2: Billion-scale tensor decompositions

    Inah Jeon;Evangelos E. Papalexakis;U Kang;Christos Faloutsos

  • GBASE: a scalable and general graph management system

    U. Kang;Hanghang Tong;Jimeng Sun;Ching-Yung Lin

  • HADI: Mining Radii of Large Graphs

    U. Kang;Charalampos E. Tsourakakis;Ana Paula Appel;Christos Faloutsos

  • VoG: Summarizing and understanding large graphs

    Danai Koutra;U Kang;Jilles Vreeken;Christos Faloutsos

  • Unifying guilt-by-association approaches: theorems and fast algorithms

    Danai Koutra;Tai-You Ke;U. Kang;Duen Horng Polo Chau

  • SIDE: Representation Learning in Signed Directed Networks

    Junghwan Kim;Haekyu Park;Ji-Eun Lee;U Kang

  • Fast random walk graph kernel

    U. Kang;Hanghang Tong;Jimeng Sun

  • Accurate Multivariate Stock Movement Prediction via Data-Axis Transformer with Multi-Level Contexts

    Jaemin Yoo;Yejun Soun;Yong-chan Park;U Kang

  • Spectral analysis for billion-scale graphs: discoveries and implementation

    U. Kang;Brendan Meeder;Christos Faloutsos

  • MASCOT: Memory-efficient and Accurate Sampling for Counting Local Triangles in Graph Streams

    Yongsub Lim;U Kang

  • Summarizing and understanding large graphs

    Danai Koutra;U Kang;Jilles Vreeken;Christos Faloutsos

  • BEAR: Block Elimination Approach for Random Walk with Restart on Large Graphs

    Kijung Shin;Jinhong Jung;Sael Lee;U. Kang

Frequent Co-Authors

Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
Hanghang Tong
Hanghang Tong University of Illinois at Urbana-Champaign
Duen Horng Chau
Duen Horng Chau Georgia Institute of Technology
Danai Koutra
Danai Koutra University of Michigan–Ann Arbor
Leman Akoglu
Leman Akoglu Carnegie Mellon University
Evangelos E. Papalexakis
Evangelos E. Papalexakis University of California, Riverside
Ching-Yung Lin
Ching-Yung Lin National Chi Nan University
Jilles Vreeken
Jilles Vreeken Max Planck Society
Marco Zaffalon
Marco Zaffalon Dalle Molle Institute for Artificial Intelligence Research
Rasmus Pagh
Rasmus Pagh University of Copenhagen

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 online education opens up numerous options for those interested in computer science. For students seeking a shorter commitment, 2 year online degrees can provide a strong foundation in the field. These programs cover essential skills and often lead to entry-level IT roles.

Many professionals choose to advance their careers with a master’s degree. There are several quick masters degrees online that allow for flexible learning and faster completion, making it easier to balance work and study. A master’s in computer science is consistently ranked among the most useful graduate degrees, leading to in-demand job opportunities in tech, data science, and cybersecurity.

Cost is often a concern. Thankfully, numerous affordable online degree programs are available, enabling students to pursue high-quality education without overwhelming debt. Whether you choose an associate, bachelor’s, or master’s degree, online pathways in computer science offer flexibility and the potential for a rewarding career.

Best Scientists Citing U Kang

Trending Scientists

Recently Published Articles