World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
55
Citations
9266
World Ranking
4402
National Ranking
2055

Yisong Yue 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 Yisong Yue 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: 179 publications — 38th percentile

38% of scientists in this discipline score the same or lower.

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

Yisong Yue 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 Yisong Yue 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: 55 D-Index — 71st percentile

71% of scientists in this discipline score the same or lower.

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

Overview

Yisong Yue is affiliated with the California Institute of Technology in the United States. The primary fields of study encompass Computer Science and Engineering, with significant contributions in subfields such as Artificial Intelligence, Control and Systems Engineering, Molecular Biology, Computer Vision and Pattern Recognition, and Biomedical Engineering.

The research work focuses on topics including Reinforcement Learning in Robotics, Machine Learning and Algorithms, Advanced Control Systems Optimization, Fault Detection and Control Systems, Robotic Path Planning Algorithms, Advanced Bandit Algorithms Research, and Formal Methods in Verification.

Yisong Yue has published extensively in several venues. Frequent publication venues include arXiv (Cornell University), bioRxiv (Cold Spring Harbor Laboratory), IEEE Robotics and Automation Letters, Cell Systems, and The Caltech Institute Archives (California Institute of Technology).

Among recent papers, notable works include:

  • "Informed training set design enables efficient machine learning-assisted directed protein evolution," 2021, Cell Systems
  • "Neural-Fly enables rapid learning for agile flight in strong winds," 2022, Science Robotics
  • "Using deep reinforcement learning to reveal how the brain encodes abstract state-space representations in high-dimensional environments," 2020, Neuron
  • "Neural-Swarm2: Planning and Control of Heterogeneous Multirotor Swarms Using Learned Interactions," 2021, IEEE Transactions on Robotics
  • "An Efficient Simulation-Based Approach to Ambulance Fleet Allocation and Dynamic Redeployment," 2021, Proceedings of the AAAI Conference on Artificial Intelligence

Yisong Yue's frequent coauthors include Aaron D. Ames, Soon-Jo Chung, Guanya Shi, Frances H. Arnold, and Victor D. Dorobantu.

Best Publications

  • A support vector method for optimizing average precision

    Yisong Yue;Thomas Finley;Filip Radlinski;Thorsten Joachims

  • The K-armed dueling bandits problem

    Yisong Yue;Josef Broder;Robert Kleinberg;Thorsten Joachims

  • Interactively optimizing information retrieval systems as a dueling bandits problem

    Yisong Yue;Thorsten Joachims

  • A deep learning approach for generalized speech animation

    Sarah Taylor;Taehwan Kim;Yisong Yue;Moshe Mahler

  • Neural Lander: Stable Drone Landing Control Using Learned Dynamics

    Guanya Shi;Xichen Shi;Michael O'Connell;Rose Yu

  • Multi-Level Structured Models for Document-Level Sentiment Classification

    Ainur Yessenalina;Yisong Yue;Claire Cardie

  • Large-scale validation and analysis of interleaved search evaluation

    Olivier Chapelle;Thorsten Joachims;Filip Radlinski;Yisong Yue

  • Beyond position bias: examining result attractiveness as a source of presentation bias in clickthrough data

    Yisong Yue;Rajan Patel;Hein Roehrig

  • Predicting diverse subsets using structural SVMs

    Yisong Yue;Thorsten Joachims

  • Reliable Real-Time Seismic Signal/Noise Discrimination With Machine Learning

    Men‐Andrin Meier;Zachary E. Ross;Anshul Ramachandran;Ashwin Balakrishna

  • PhaseLink: A Deep Learning Approach to Seismic Phase Association

    Zachary E. Ross;Yisong Yue;Men-Andrin Meier;Egill Hauksson

  • Large-Scale Analysis of Soccer Matches Using Spatiotemporal Tracking Data

    Alina Bialkowski;Patrick Lucey;Peter Carr;Yisong Yue

  • Informed training set design enables efficient machine learning-assisted directed protein evolution.

    Bruce J. Wittmann;Yisong Yue;Frances H. Arnold

  • Linear Submodular Bandits and their Application to Diversified Retrieval

    Yisong Yue;Carlos Guestrin

  • Learning for Safety-Critical Control with Control Barrier Functions

    Andrew J. Taylor;Andrew Singletary;Yisong Yue;Aaron D. Ames

  • Predicting structured objects with support vector machines

    Thorsten Joachims;Thomas Hofmann;Yisong Yue;Chun-Nam Yu

  • Batch Policy Learning under Constraints

    Hoang Minh Le;Cameron Voloshin;Yisong Yue

  • Coordinated multi-agent imitation learning

    Hoang M. Le;Yisong Yue;Peter Carr;Patrick Lucey

  • Long-term Forecasting using Tensor-Train RNNs

    Rose Yu;Stephan Zheng;Anima Anandkumar;Yisong Yue

  • Learning Fine-Grained Spatial Models for Dynamic Sports Play Prediction

    Yisong Yue;Patrick Lucey;Peter Carr;Alina Bialkowski

  • Beat the Mean Bandit

    Yisong Yue;Thorsten Joachims

  • Interactively Optimizing Information Retrieval Systemsas a Dueling Bandits Problem

    Yisong Yue;Thorsten Joachims

Frequent Co-Authors

Anima Anandkumar
Anima Anandkumar Nvidia (United Kingdom)
Soon-Jo Chung
Soon-Jo Chung California Institute of Technology
Aaron D. Ames
Aaron D. Ames California Institute of Technology
Joel W. Burdick
Joel W. Burdick California Institute of Technology
Patrick Lucey
Patrick Lucey Stats Perform
Peter W. Carr
Peter W. Carr University of Minnesota
Pietro Perona
Pietro Perona California Institute of Technology
Thorsten Joachims
Thorsten Joachims Cornell University
Iain Matthews
Iain Matthews University of East Anglia
Swarat Chaudhuri
Swarat Chaudhuri The University of Texas at Austin

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