World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
89
Citations
126916
World Ranking
622
National Ranking
330

Kyunghyun Cho 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 Kyunghyun Cho 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: 305 publications — 75th percentile

75% of scientists in this discipline score the same or lower.

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

Kyunghyun Cho 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 Kyunghyun Cho 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: 89 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

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

Overview

Kyunghyun Cho is affiliated with New York University in the United States. Their research primarily spans the field of computer science, with a focus on artificial intelligence, molecular biology, computer vision and pattern recognition, surgery, and radiology, nuclear medicine, and imaging.

The scientist's work encompasses several major research topics including topic modeling, natural language processing techniques, total knee arthroplasty outcomes, protein structure and dynamics, machine learning in bioinformatics, radiomics and machine learning in medical imaging, and multimodal machine learning applications.

Frequent coauthors in their collaborations include Richard Bonneau, Vladimir Gligorijević, Haresh Rengaraj Rajamohan, Krzysztof J. Geras, and Nathan C. Frey.

Kyunghyun Cho has contributed to numerous publications, often appearing in several key venues. The frequent publication venues are:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition
  • Zenodo (CERN European Organization for Nuclear Research)
  • Proceedings of the AAAI Conference on Artificial Intelligence

Selected recent papers include:

  • Static Analysis of Shape in TensorFlow Programs, 2020, arXiv (Cornell University)
  • Structure-based protein function prediction using graph convolutional networks, 2021, Nature Communications
  • Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms, 2020, JAMA Network Open
  • Health system-scale language models are all-purpose prediction engines, 2023, Nature
  • Prediction of Total Knee Replacement and Diagnosis of Osteoarthritis by Using Deep Learning on Knee Radiographs: Data from the Osteoarthritis Initiative, 2020, Radiology

Best Publications

  • Learning Phrase Representations using RNN Encoder--Decoder for Statistical Machine Translation

    Kyunghyun Cho;Bart van Merrienboer;Caglar Gulcehre;Dzmitry Bahdanau

  • Neural Machine Translation by Jointly Learning to Align and Translate

    Dzmitry Bahdanau;Kyunghyun Cho;Yoshua Bengio

  • Empirical evaluation of gated recurrent neural networks on sequence modeling

    Junyoung Chung;Çaglar Gülçehre;KyungHyun Cho;Yoshua Bengio;Yoshua Bengio;Yoshua Bengio

  • Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

    Kelvin Xu;Jimmy Ba;Ryan Kiros;Kyunghyun Cho

  • On the Properties of Neural Machine Translation: Encoder--Decoder Approaches

    Kyunghyun Cho;Bart van Merrienboer;Dzmitry Bahdanau;Yoshua Bengio;Yoshua Bengio;Yoshua Bengio

  • Show, Attend and Tell: Neural Image Caption Generation with Visual Attention

    Kelvin Xu;Jimmy Ba;Ryan Kiros;Kyunghyun Cho

  • Attention-based models for speech recognition

    Jan Chorowski;Dzmitry Bahdanau;Dmitriy Serdyuk;Kyunghyun Cho

  • Recurrent Neural Networks for Multivariate Time Series with Missing Values.

    Zhengping Che;Sanjay Purushotham;Kyunghyun Cho;David A. Sontag

  • Theano: A Python framework for fast computation of mathematical expressions

    Rami Al-Rfou;Guillaume Alain;Amjad Almahairi

  • Identifying and attacking the saddle point problem in high-dimensional non-convex optimization

    Yann N Dauphin;Razvan Pascanu;Caglar Gulcehre;Kyunghyun Cho

  • Describing Videos by Exploiting Temporal Structure

    Li Yao;Atousa Torabi;Kyunghyun Cho;Nicolas Ballas

  • On the Number of Linear Regions of Deep Neural Networks

    Guido F Montufar;Razvan Pascanu;Kyunghyun Cho;Yoshua Bengio

  • On Using Very Large Target Vocabulary for Neural Machine Translation

    Sébastien Jean;Kyunghyun Cho;Roland Memisevic;Yoshua Bengio

  • How to Construct Deep Recurrent Neural Networks

    Razvan Pascanu;Caglar Gulcehre;Kyunghyun Cho;Yoshua Bengio

  • Structure-based protein function prediction using graph convolutional networks.

    Vladimir Gligorijević;P. Douglas Renfrew;Tomasz Kosciolek;Tomasz Kosciolek;Julia Koehler Leman

  • Gated Feedback Recurrent Neural Networks

    Junyoung Chung;Caglar Gulcehre;Kyunghyun Cho;Yoshua Bengio;Yoshua Bengio

  • Augmentation for small object detection

    Mate Kisantal;Zbigniew Wojna;Jakub Murawski;Jacek Naruniec

  • On using monolingual corpora in neural machine translation

    Çaglar Gülçehre;Orhan Firat;Kelvin Xu;Kyunghyun Cho

  • Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism

    Orhan Firat;Kyunghyun Cho;Yoshua Bengio

  • Joint Event Extraction via Recurrent Neural Networks

    Thien Huu Nguyen;Kyunghyun Cho;Ralph Grishman

  • Passage Re-ranking with BERT

    Rodrigo Nogueira;Kyunghyun Cho

  • Learning distributed representations of sentences from unlabelled data

    Felix Hill;Kyunghyun Cho;Anna Korhonen

Frequent Co-Authors

Yoshua Bengio
Yoshua Bengio University of Montreal
Jason Weston
Jason Weston Facebook (United States)
Douwe Kiela
Douwe Kiela Stanford University
Caglar Gulcehre
Caglar Gulcehre DeepMind (United Kingdom)
Aaron Courville
Aaron Courville University of Montreal
Samuel R. Bowman
Samuel R. Bowman New York University
Jiatao Gu
Jiatao Gu Apple (United States)
Victor O. K. Li
Victor O. K. Li University of Hong Kong
Mark Sandler
Mark Sandler Google (United States)
Razvan Pascanu
Razvan Pascanu DeepMind (United Kingdom)

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