World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
49
Citations
8933
World Ranking
5923
National Ranking
2674

Kesheng Wu 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 Kesheng Wu 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: 236 publications — 58th percentile

58% of scientists in this discipline score the same or lower.

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

Kesheng Wu 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 Kesheng Wu 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: 49 D-Index — 60th percentile

60% 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

  • 2010 - ACM Distinguished Member
  • 2007 - ACM Senior Member

Overview

Kesheng Wu is affiliated with the Lawrence Berkeley National Laboratory in the United States. The primary research focus is in Computer Science, with more than 100 publications in the field. Within this domain, prominent subfields include Computer Networks and Communications, Artificial Intelligence, Hardware and Architecture, Electrical and Electronic Engineering, and Surgery. The main topics of research cover a diverse range of areas such as Advanced Data Storage Technologies, Distributed and Parallel Computing Systems, Parallel Computing and Optimization Techniques, Anomaly Detection Techniques and Applications, Scientific Computing and Data Management, Network Security and Intrusion Detection, and Seismic Waves and Analysis.

The scientist has contributed to numerous papers, including:

  • ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management (2020, SoftwareX)
  • Enhancing IoT anomaly detection performance for federated learning (2022, Digital Communications and Networks)
  • Improving I/O Performance for Exascale Applications Through Online Data Layout Reorganization (2021, IEEE Transactions on Parallel and Distributed Systems)
  • The Imperial Valley Dark Fiber Project: Toward Seismic Studies Using DAS and Telecom Infrastructure for Geothermal Applications (2022, Seismological Research Letters)
  • Real-time and post-hoc compression for data from Distributed Acoustic Sensing (2022, Computers & Geosciences)

Frequent collaborators include Alex Sim, Suren Byna, Junmin Gu, Bin Dong, and Alina Lazar.

Kesheng Wu's publications have appeared often in a set of notable venues, including arXiv (Cornell University), EPJ Web of Conferences, IEEE Access, Information Sciences, and Sensors.

Additionally, Kesheng Wu has authored a book published by Springer Nature titled User-Defined Tensor Data Analysis (2021).

Recognition of professional standing is reflected in awards such as the ACM Distinguished Member (2010) and ACM Senior Member (2007).

Best Publications

  • Higher-order finite-difference pseudopotential method: An application to diatomic molecules

    James R. Chelikowsky;N. Troullier;K. Wu;Y. Saad

  • Fast connected-component labeling

    Lifeng He;Yuyan Chao;Kenji Suzuki;Kesheng Wu

  • Optimizing bitmap indices with efficient compression

    Kesheng Wu;Ekow J. Otoo;Arie Shoshani

  • Thick-Restart Lanczos Method for Large Symmetric Eigenvalue Problems

    Kesheng Wu;Horst Simon

  • Optimizing two-pass connected-component labeling algorithms

    Kesheng Wu;Ekow Otoo;Kenji Suzuki

  • Optimizing connected component labeling algorithms

    Kesheng Wu;Ekow J. Otoo;Arie Shoshani

  • Hello ADIOS: the challenges and lessons of developing leadership class I/O frameworks

    Qing Liu;Jeremy Logan;Yuan Tian;Hasan Abbasi

  • On the performance of bitmap indices for high cardinality attributes

    Kesheng Wu;Ekow Otoo;Arie Shoshani

  • Solving the Optimal Trading Trajectory Problem Using a Quantum Annealer

    Gili Rosenberg;Poya Haghnegahdar;Phil Goddard;Peter Carr

  • FastBit: interactively searching massive data

    K. Wu;S. Ahern;E. W. Bethel;E. W. Bethel;J. Chen

  • ADIOS 2: The Adaptable Input Output System. A framework for high-performance data management

    William F. Godoy;Norbert Podhorszki;Ruonan Wang;Chuck Atkins

  • Compressing bitmap indexes for faster search operations

    Kesheng Wu;E.J. Otoo;A. Shoshani

  • Dynamic Thick Restarting of the Davidson, and the Implicitly Restarted Arnoldi Methods

    Andreas Stathopoulos;Yousef Saad;Kesheng Wu

  • Query-driven visualization of large data sets

    K. Stockinger;J. Shalf;K. Wu;E.W. Bethel

  • A Block Orthogonalization Procedure with Constant Synchronization Requirements

    Andreas Stathopoulos;Kesheng Wu

  • Ab initio molecular-dynamics simulations of Si clusters using the higher-order finite-difference-pseudopotential method

    Xiaodun Jing;N. Troullier;David Dean;N. Binggeli

  • Parallel data analysis directly on scientific file formats

    Spyros Blanas;Kesheng Wu;Surendra Byna;Bin Dong

  • Using bitmap index for interactive exploration of large datasets

    Kesheng Wu;Wendy Koegler;Jacqueline Chen;Arie Shoshani

  • Parallel index and query for large scale data analysis

    Jerry Chou;Mark Howison;Brian Austin;Kesheng Wu

  • HDF5-FastQuery: Accelerating Complex Queries on HDF Datasets using Fast Bitmap Indices

    L. Gosink;J. Shalf;K. Stockinger;K. Wu

Frequent Co-Authors

Arie Shoshani
Arie Shoshani Lawrence Berkeley National Laboratory
Kurt Stockinger
Kurt Stockinger Zurich University of Applied Sciences
Horst D. Simon
Horst D. Simon Lawrence Berkeley National Laboratory
Suren Byna
Suren Byna The Ohio State University
Scott Klasky
Scott Klasky Oak Ridge National Laboratory
Bernd Hamann
Bernd Hamann University of California, Davis
Doron Rotem
Doron Rotem Lawrence Berkeley National Laboratory
Yousef Saad
Yousef Saad University of Minnesota
John Shalf
John Shalf Lawrence Berkeley National Laboratory
Peter Nugent
Peter Nugent Lawrence Berkeley National Laboratory

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