World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
43
Citations
8223
World Ranking
7957
National Ranking
3427

Weng-Keen Wong 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 Weng-Keen Wong 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: 98 publications — 8th percentile

8% of scientists in this discipline score the same or lower.

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

Weng-Keen Wong 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 Weng-Keen Wong 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: 43 D-Index — 46th percentile

46% 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

  • 2007 - Fellow of the American Statistical Association (ASA)

Overview

Weng-Keen Wong is affiliated with Oregon State University in the United States and has made contributions primarily in the field of Computer Science. Their research encompasses diverse subfields including Artificial Intelligence, Nuclear and High Energy Physics, Computational Theory and Mathematics, Economics and Econometrics, and Radiation.

The scientist has published extensively in various venues, with frequent publications appearing in:

  • arXiv (Cornell University)
  • Artificial Intelligence
  • Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment
  • ACM Transactions on Knowledge Discovery from Data
  • IEEE Access

Weng-Keen Wong's research topics cover a broad array of areas, including:

  • Anomaly Detection Techniques and Applications
  • Wireless Signal Modulation Classification
  • Laser-Plasma Interactions and Diagnostics
  • Explainable Artificial Intelligence (XAI)
  • Reinforcement Learning in Robotics
  • Sports Analytics and Performance
  • Nuclear Physics and Applications

Some of the recent published papers include:

  • "Counterfactual state explanations for reinforcement learning agents via generative deep learning", 2021, Artificial Intelligence
  • "Isotope identification using deep learning: An explanation", 2020, Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment
  • "Discovering Anomalies by Incorporating Feedback from an Expert", 2020, ACM Transactions on Knowledge Discovery from Data
  • "BioNeMo Framework: a modular, high-performance library for AI model development in drug discovery", 2024, arXiv (Cornell University)
  • "Deep Learning Model Portability for Domain-Agnostic Device Fingerprinting", 2023, IEEE Access

Frequent co-authors collaborating with Weng-Keen Wong include:

  • Matthew Olson
  • Fuxin Li
  • Bechir Hamdaoui
  • Shusen Liu
  • Jayaraman J. Thiagarajan

Wong's work bridges theoretical and applied aspects of artificial intelligence, with notable contributions to explainable AI and anomaly detection. Their statistical expertise was recognized with election as a Fellow of the American Statistical Association in 2007.

Best Publications

  • The eBird enterprise: An integrated approach to development and application of citizen science

    Brian L. Sullivan;Jocelyn L. Aycrigg;Jessie H. Barry;Rick E. Bonney

  • Principles of Explanatory Debugging to Personalize Interactive Machine Learning

    Todd Kulesza;Margaret Burnett;Weng-Keen Wong;Simone Stumpf

  • Data-intensive science applied to broad-scale citizen science

    Wesley M. Hochachka;Daniel Fink;Rebecca A. Hutchinson;Daniel Sheldon

  • Open Set Learning with Counterfactual Images.

    Lawrence Neal;Matthew L. Olson;Xiaoli Z. Fern;Weng-Keen Wong

  • Too much, too little, or just right? Ways explanations impact end users' mental models

    Todd Kulesza;Simone Stumpf;Margaret Burnett;Sherry Yang

  • Bayesian network anomaly pattern detection for disease outbreaks

    Weng-Keen Wong;Andrew Moore;Gregory Cooper;Michael Wagner

  • Interacting meaningfully with machine learning systems: Three experiments

    Simone Stumpf;Vidya Rajaram;Lida Li;Weng-Keen Wong

  • Machine learning for activity recognition: hip versus wrist data

    Stewart G Trost;Yonglei Zheng;Weng-Keen Wong

  • Distributed Value Functions

    Jeff G. Schneider;Weng-Keen Wong;Andrew W. Moore;Martin A. Riedmiller

  • Rule-based anomaly pattern detection for detecting disease outbreaks

    Weng-Keen Wong;Andrew Moore;Gregory Cooper;Michael Wagner

  • Detecting insider threats in a real corporate database of computer usage activity

    Ted E. Senator;Henry G. Goldberg;Alex Memory;William T. Young

  • Artificial Neural Networks to Predict Activity Type and Energy Expenditure in Youth

    Stewart G. Trost;Weng Keen Wong;Karen A. Pfeiffer;Yonglei Zheng

  • Taming compiler fuzzers

    Yang Chen;Alex Groce;Chaoqiang Zhang;Weng-Keen Wong

  • Incorporating Expert Feedback into Active Anomaly Discovery

    Shubhomoy Das;Weng-Keen Wong;Thomas Dietterich;Alan Fern

  • Optimal reinsertion: a new search operator for accelerated and more accurate Bayesian network structure learning

    Andrew Moore;Weng-Keen Wong

  • Systematic construction of anomaly detection benchmarks from real data

    Andrew F. Emmott;Shubhomoy Das;Thomas Dietterich;Alan Fern

  • Issues in applied statistics for public health bioterrorism surveillance using multiple data streams: research needs.

    Henry Rolka;Howard Burkom;Gregory F. Cooper;Martin Kulldorff

  • Explanatory Debugging: Supporting End-User Debugging of Machine-Learned Programs

    Todd Kulesza;Simone Stumpf;Margaret Burnett;Weng-Keen Wong

  • Physical activity recognition from accelerometer data using a multi-scale ensemble method

    Yonglei Zheng;Weng-Keen Wong;Xinze Guan;Stewart Trost

  • Computational sustainability: computing for a better world and a sustainable future

    Carla Gomes;Thomas Dietterich;Christopher Barrett;Jon Conrad

  • WSARE: What's Strange About Recent Events?

    Weng-Keen Wong;Andrew Moore;Gregory Cooper;Michael Wagner

Frequent Co-Authors

Margaret Burnett
Margaret Burnett Oregon State University
Thomas G. Dietterich
Thomas G. Dietterich Oregon State University
Alan Fern
Alan Fern Oregon State University
Michael Wagner
Michael Wagner TU Dresden
Andrew W. Moore
Andrew W. Moore Carnegie Mellon University
Gregory F. Cooper
Gregory F. Cooper University of Pittsburgh
Xiaoli Z. Fern
Xiaoli Z. Fern Oregon State University
Carl Lagoze
Carl Lagoze University of Michigan–Ann Arbor
Carla P. Gomes
Carla P. Gomes Cornell University
Alex Groce
Alex Groce Northern Arizona University

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