World's Best Scientists 2026 revealed!
Seong-Whan Lee

Seong-Whan Lee

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Computer Science
Korea
2026

D-Index & Metrics

Computer Science

D-Index
82
Citations
25454
World Ranking
968
National Ranking
3

Seong-Whan Lee 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 Seong-Whan Lee 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: 664 publications — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Seong-Whan Lee 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 Seong-Whan Lee 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: 82 D-Index — 94th percentile

94% 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

  • 2026 - Research.com Computer Science in Korea Leader Award
  • 2025 - Research.com Computer Science in Korea Leader Award
  • 2024 - Research.com Computer Science in Korea Leader Award
  • 2023 - Fellow of the National Academy of Engineering of Korea (NAEK)
  • 2023 - Fellow of the National Academy of Engineering of Korea (NAEK)
  • 2023 - Research.com Computer Science in Korea Leader Award
  • 2022 - Research.com Computer Science in Korea Leader Award
  • 2010 - IEEE Fellow For contributions to pattern recognition for biometrics and document image analysis
  • 2009 - Fellow of the Korean Academy of Science and Technology (KAST)
  • 1998 - Fellow of the International Association for Pattern Recognition (IAPR) For contributions to document understanding and for service to IAPR

Overview

Seong-Whan Lee is affiliated with Korea University in South Korea and has an extensive publication record primarily in the fields of Computer Science and Neuroscience. Their work spans several subfields including Cognitive Neuroscience, Artificial Intelligence, Computer Vision and Pattern Recognition, Signal Processing, and Electrical and Electronic Engineering.

The research topics covered by Seong-Whan Lee focus mainly on EEG and Brain-Computer Interfaces, Advanced Memory and Neural Computing, Neural Dynamics and Brain Function, Gaze Tracking and Assistive Technology, Speech Recognition and Synthesis, Human Pose and Action Recognition, and Functional Brain Connectivity Studies.

Some of the recent papers authored include:

  • Brain-Controlled Robotic Arm System Based on Multi-Directional CNN-BiLSTM Network Using EEG Signals, 2020, IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • Adaptive Transfer Learning for EEG Motor Imagery Classification with Deep Convolutional Neural Network, 2020, Neural Networks
  • Spatio-Spectral Feature Representation for Motor Imagery Classification Using Convolutional Neural Networks, 2021, IEEE Transactions on Neural Networks and Learning Systems
  • Neural Decoding of Imagined Speech and Visual Imagery as Intuitive Paradigms for BCI Communication, 2020, IEEE Transactions on Neural Systems and Rehabilitation Engineering
  • FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface, 2021, arXiv (Cornell University)

Frequent co-authors in their collaborative work include Ji-Hoon Jeong, Minji Lee, Dinggang Shen, Woo-Jeoung Nam, and Gi-Hwan Shin.

The scientist often publishes in venues such as arXiv (Cornell University), UNC Libraries, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Neural Networks, and Pattern Recognition.

Seong-Whan Lee has received several awards recognizing their contributions to the scientific community. These include being named an IEEE Fellow in 2010 for contributions to pattern recognition related to biometrics and document image analysis, a Fellow of the Korean Academy of Science and Technology (KAST) in 2009, and a Fellow of the International Association for Pattern Recognition (IAPR) in 1998 for contributions to document understanding and professional service.

Best Publications

  • Thinning methodologies—a comprehensive survey

    Louisa Lam;Seong-Whan Lee;Ching Y. Suen

  • The Role of Context for Object Detection and Semantic Segmentation in the Wild

    Roozbeh Mottaghi;Xianjie Chen;Xiaobai Liu;Nam-Gyu Cho

  • Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis.

    Heung-Il Suk;Seong-Whan Lee;Dinggang Shen

  • Latent feature representation with stacked auto-encoder for AD/MCI diagnosis

    Heung Il Suk;Seong Whan Lee;Dinggang Shen;Dinggang Shen

  • Applications of Support Vector Machines for Pattern Recognition: A Survey

    Hyeran Byun;Seong-Whan Lee

  • EEG dataset and OpenBMI toolbox for three BCI paradigms: an investigation into BCI illiteracy.

    Minho Lee;O-Yeon Kwon;Yong-Jeong Kim;Hong-Kyung Kim

  • Advances in Biometrics

    Seong-Whan Lee;Stan Z. Li

  • State-space model with deep learning for functional dynamics estimation in resting-state fMRI

    Heung Il Suk;Chong Yaw Wee;Seong Whan Lee;Dinggang Shen

  • Subject-Independent Brain–Computer Interfaces Based on Deep Convolutional Neural Networks

    O-Yeon Kwon;Min-Ho Lee;Cuntai Guan;Seong-Whan Lee

  • Deep ensemble learning of sparse regression models for brain disease diagnosis

    Heung Il Suk;Seong Whan Lee;Dinggang Shen;Dinggang Shen

  • Biologically Motivated Computer Vision: Second International Workshop

    HH Bülthoff;Lee S-W, Poggio, Ta;C Wallraven

  • Off-line recognition of totally unconstrained handwritten numerals using multilayer cluster neural network

    Seong-Whan Lee

  • A convolutional neural network for steady state visual evoked potential classification under ambulatory environment.

    No Sang Kwak;Klaus Robert Müller;Klaus Robert Müller;Seong Whan Lee

  • Sign Language Spotting with a Threshold Model Based on Conditional Random Fields

    H.-D. Yang;S. Sclaroff;S.-W. Lee

  • A SURVEY ON PATTERN RECOGNITION APPLICATIONS OF SUPPORT VECTOR MACHINES

    Hyeran Byun;Seong Whan Lee

  • AdaBoost for Text Detection in Natural Scene

    Jung-Jin Lee;Pyoung-Hean Lee;Seong-Whan Lee;Alan Yuille

  • Brain-Controlled Robotic Arm System Based on Multi-Directional CNN-BiLSTM Network Using EEG Signals

    Ji-Hoon Jeong;Kyung-Hwan Shim;Dong-Joo Kim;Seong-Whan Lee

  • A Novel Bayesian Framework for Discriminative Feature Extraction in Brain-Computer Interfaces

    Heung-Il Suk;Seong-Whan Lee

  • Adaptive transfer learning for EEG motor imagery classification with deep Convolutional Neural Network.

    Kaishuo Zhang;Neethu Robinson;Seong Whan Lee;Cuntai Guan

  • A novel relational regularization feature selection method for joint regression and classification in AD diagnosis

    Xiaofeng Zhu;Heung-Il Suk;Li Wang;Seong-Whan Lee

  • A new methodology for gray-scale character segmentation and recognition

    Seong-Whan Lee;Dong-June Lee;Dong-June Lee;Hee-Seon Park;Hee-Seon Park

  • Hand gesture recognition based on dynamic Bayesian network framework

    Heung-Il Suk;Bong-Kee Sin;Seong-Whan Lee

  • Fast scene change detection using direct feature extraction from MPEG compressed videos

    Seong-Whan Lee;Young-Min Kim;Sung Woo Choi

Frequent Co-Authors

Dinggang Shen
Dinggang Shen ShanghaiTech University
Heung-Il Suk
Heung-Il Suk Korea University
Klaus-Robert Müller
Klaus-Robert Müller Technical University of Berlin
Anil K. Jain
Anil K. Jain Michigan State University
Yuan Yan Tang
Yuan Yan Tang University of Macau
Heinrich H. Bülthoff
Heinrich H. Bülthoff Max Planck Institute for Biological Cybernetics
Christian Wallraven
Christian Wallraven Korea University
Han Zhang
Han Zhang ShanghaiTech University
Cuntai Guan
Cuntai Guan Nanyang Technological University
Giulio Tononi
Giulio Tononi University of Wisconsin–Madison

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