World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
10529
World Ranking
7452
National Ranking
3247

Sewoong Oh 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 Sewoong Oh 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: 146 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

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

Sewoong Oh 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 Sewoong Oh 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: 44 D-Index — 48th percentile

48% of scientists in this discipline score the same or lower.

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

Overview

Sewoong Oh is affiliated with the University of Washington in the United States. Their research primarily spans the field of Computer Science, with substantial contributions across several subfields. These subfields include Artificial Intelligence, Molecular Biology, Spectroscopy, Computer Networks and Communications, and Computer Vision and Pattern Recognition.

The scientist's work addresses numerous topics, with a particular emphasis on:

  • Privacy-Preserving Technologies in Data
  • Advanced Proteomics Techniques and Applications
  • Mass Spectrometry Techniques and Applications
  • Stochastic Gradient Optimization Techniques
  • Adversarial Robustness in Machine Learning
  • Error Correcting Code Techniques
  • Domain Adaptation and Few-Shot Learning

They have contributed to a variety of published research articles. Notable recent papers include:

  • Sequence-to-sequence translation from mass spectra to peptides with a transformer model, 2024, Nature Communications
  • DataComp: In search of the next generation of multimodal datasets, 2023, arXiv (Cornell University)
  • Deepcode: Feedback Codes via Deep Learning, 2020, IEEE Journal on Selected Areas in Information Theory
  • PacGAN: The Power of Two Samples in Generative Adversarial Networks, 2020, IEEE Journal on Selected Areas in Information Theory
  • Physical Layer Communication via Deep Learning, 2020, IEEE Journal on Selected Areas in Information Theory

The scientist frequently publishes in venues such as:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • IEEE Journal on Selected Areas in Information Theory
  • Journal of Proteome Research
  • Cancer Research

Frequent collaborators in their research include:

  • Pramod Viswanath
  • William Stafford Noble
  • Xiyang Liu
  • Peter Kairouz
  • Jonathan Hayase

Best Publications

  • Matrix Completion From a Few Entries

    Raghunandan H Keshavan;Andrea Montanari;Sewoong Oh

  • Matrix Completion from Noisy Entries

    Raghunandan H. Keshavan;Andrea Montanari;Sewoong Oh

  • Iterative Learning for Reliable Crowdsourcing Systems

    David R. Karger;Sewoong Oh;Devavrat Shah

  • The Composition Theorem for Differential Privacy

    Peter Kairouz;Sewoong Oh;Pramod Viswanath

  • Budget-Optimal Task Allocation for Reliable Crowdsourcing Systems

    David R. Karger;Sewoong Oh;Devavrat Shah

  • Extremal mechanisms for local differential privacy

    Peter Kairouz;Sewoong Oh;Pramod Viswanath

  • PacGAN: The power of two samples in generative adversarial networks

    Zinan Lin;Ashish Khetan;Giulia C. Fanti;Sewoong Oh

  • Attention-based Graph Neural Network for Semi-supervised Learning

    Kiran Koshy Thekumparampil;Chong Wang;Sewoong Oh;Li-Jia Li

  • Iterative ranking from pair-wise comparisons

    Sahand Negahban;Sewoong Oh;Devavrat Shah

  • Rank Centrality: Ranking from Pairwise Comparisons

    Sahand Negahban;Sewoong Oh;Devavrat Shah

  • Matrix completion from a few entries

    Raghunandan H. Keshavan;Sewoong Oh;Andrea Montanari

  • Efficient crowdsourcing for multi-class labeling

    David R. Karger;Sewoong Oh;Devavrat Shah

  • Provable Tensor Factorization with Missing Data

    Prateek Jain;Sewoong Oh

  • The Staircase Mechanism in Differential Privacy

    Quan Geng;Peter Kairouz;Sewoong Oh;Pramod Viswanath

  • Communication algorithms via deep learning

    Hyeji Kim;Yihan Jiang;Ranvir B. Rana;Sreeram Kannan

  • Budget-optimal crowdsourcing using low-rank matrix approximations

    David R. Karger;Sewoong Oh;Devavrat Shah

  • Deepcode: Feedback Codes via Deep Learning

    Hyeji Kim;Yihan Jiang;Sreeram Kannan;Sewoong Oh

  • Counting with the crowd

    Adam Marcus;David Karger;Samuel Madden;Robert Miller

  • Demystifying Fixed $k$ -Nearest Neighbor Information Estimators

    Weihao Gao;Sewoong Oh;Pramod Viswanath

  • Estimating Mutual Information for Discrete-Continuous Mixtures

    Weihao Gao;Sreeram Kannan;Sewoong Oh;Pramod Viswanath

  • Turbo Autoencoder: Deep learning based channel codes for point-to-point communication channels

    Yihan Jiang;Hyeji Kim;Himanshu Asnani;Sreeram Kannan

Frequent Co-Authors

Pramod Viswanath
Pramod Viswanath Princeton University
Andrea Montanari
Andrea Montanari Stanford University
Yung Yi
Yung Yi Korea Advanced Institute of Science and Technology
Jinwoo Shin
Jinwoo Shin Korea Advanced Institute of Science and Technology
Sham M. Kakade
Sham M. Kakade Harvard University
Praneeth Netrapalli
Praneeth Netrapalli Google (United States)
Prateek Jain
Prateek Jain Google (United States)
Martin Vetterli
Martin Vetterli École Polytechnique Fédérale de Lausanne

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