World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
88
Citations
103747
World Ranking
654
National Ranking
347

Kai Li 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 Kai Li 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: 215 publications — 52nd percentile

52% of scientists in this discipline score the same or lower.

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

Kai Li 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 Kai Li 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: 88 D-Index — 95th percentile

95% 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

  • 2012 - Member of the National Academy of Engineering For advances in data storage and distributed computer systems.
  • 1998 - ACM Fellow For fundamental contributions to computer systems and architecture, by introducing and demonstrating the effectiveness of Shared Virtual Memory.

Overview

Kai Li is a researcher affiliated with Princeton University in the United States. Their work spans multiple areas within computer science and neuroscience, with a focus on artificial intelligence and cognitive neuroscience among other specialized fields.

The primary fields of study for Kai Li include:

  • Computer Science
  • Neuroscience

Within these main fields, their subfields of study further specify their research interests as:

  • Artificial Intelligence
  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience
  • Biophysics
  • Structural Biology

Kai Li's research addresses several key topics, including:

  • Neural dynamics and brain function
  • Neuroscience and Neuropharmacology Research
  • Privacy-Preserving Technologies in Data
  • Advanced Electron Microscopy Techniques and Applications
  • Cell Image Analysis Techniques
  • Adversarial Robustness in Machine Learning
  • Neurobiology and Insect Physiology Research

Their recent publications highlight a blend of neuroscience and computer science approaches:

  • "Functional connectomics spanning multiple areas of mouse visual cortex" (2025), published in Nature
  • "Cell-type-specific inhibitory circuitry from a connectomic census of mouse visual cortex" (2023), published in bioRxiv (Cold Spring Harbor Laboratory)
  • "Exploring Deep-Reinforcement-Learning-Assisted Federated Learning for Online Resource Allocation in Privacy-Preserving EdgeIoT" (2022), published in IEEE Internet of Things Journal
  • "Sparse multi-output Gaussian processes for online medical time series prediction" (2020), published in BMC Medical Informatics and Decision Making
  • "Petascale neural circuit reconstruction: automated methods" (2021), published in bioRxiv (Cold Spring Harbor Laboratory)

The venues where Kai Li frequently publishes indicate a presence in high-impact and specialized platforms focused on scientific and technical research:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Nature
  • Zenodo (CERN European Organization for Nuclear Research)
  • Nature Communications

Kai Li has collaborated extensively with several coauthors, including:

  • J. Alexander Bae
  • Nico Kemnitz
  • Thomas Macrina
  • Eric Mitchell
  • Shang Mu

Kai Li's recognized contributions extend to honors such as:

  • Member of the National Academy of Engineering (2012) for advances in data storage and distributed computer systems
  • ACM Fellow (1998) for fundamental contributions to computer systems and architecture, especially involving shared virtual memory

Best Publications

  • ImageNet: A large-scale hierarchical image database

    Jia Deng;Wei Dong;Richard Socher;Li-Jia Li

  • The PARSEC benchmark suite: characterization and architectural implications

    Christian Bienia;Sanjeev Kumar;Jaswinder Pal Singh;Kai Li

  • Search and replication in unstructured peer-to-peer networks

    Qin Lv;Pei Cao;Edith Cohen;Kai Li

  • Memory coherence in shared virtual memory systems

    Kai Li;Paul Hudak

  • Search and replication in unstructured peer-to-peer networks

    Unknown

  • Benchmarking modern multiprocessors

    Kai Li;Christian Bienia

  • Avoiding the disk bottleneck in the data domain deduplication file system

    Benjamin Zhu;Kai Li;Hugo Patterson

  • Multi-probe LSH: efficient indexing for high-dimensional similarity search

    Qin Lv;William Josephson;Zhe Wang;Moses Charikar

  • Libckpt: transparent checkpointing under Unix

    James S. Plank;Micah Beck;Gerry Kingsley;Kai Li

  • Efficient k-nearest neighbor graph construction for generic similarity measures

    Wei Dong;Charikar Moses;Kai Li

  • Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma

    Michael A. Gillette;Michael A. Gillette;Shankha Satpathy;Song Cao;Saravana M. Dhanasekaran

  • Integrated Proteogenomic Characterization of Clear Cell Renal Cell Carcinoma.

    David J. Clark;Saravana M. Dhanasekaran;Francesca Petralia;Jianbo Pan

  • What does classifying more than 10,000 image categories tell us?

    Jia Deng;Alexander C. Berg;Kai Li;Li Fei-Fei

  • Proteogenomic and metabolomic characterization of human glioblastoma

    Liang-Bo Wang;Alla Karpova;Marina A. Gritsenko;Jennifer E. Kyle

  • Shared virtual memory on loosely coupled multiprocessors

    Kai Li

  • IVY: A Shared Virtual Memory System for Parallel Computing.

    Kai Li

  • The Multi-Queue Replacement Algorithm for Second Level Buffer Caches

    Yuanyuan Zhou;James Philbin;Kai Li

  • Diskless checkpointing

    J.S. Plank;Kai Li;M.A. Puening

  • A study of integrated prefetching and caching strategies

    Pei Cao;Edward W. Felten;Anna R. Karlin;Kai Li

  • Real-time concurrent collection on stock multiprocessors

    A. W. Appel;J. R. Ellis;K. Li

  • Scope Consistency: A Bridge between Release Consistency and Entry Consistency

    Liviu Iftode;Jaswinder Pal Singh;Kai Li

Frequent Co-Authors

Edward W. Felten
Edward W. Felten Princeton University
Moses Charikar
Moses Charikar Stanford University
Qin Lv
Qin Lv University of Colorado Boulder
Liviu Iftode
Liviu Iftode Rutgers, The State University of New Jersey
James S. Plank
James S. Plank University of Tennessee at Knoxville
Olga G. Troyanskaya
Olga G. Troyanskaya Princeton University
Yuanyuan Zhou
Yuanyuan Zhou University of California, San Diego
Wei Dong
Wei Dong Zhejiang University
Thomas Funkhouser
Thomas Funkhouser Google (United States)
Douglas W. Clark
Douglas W. Clark Princeton University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online education options can pave diverse pathways in tech and related fields. Many students wonder, will grad schools accept low gpa? The good news is, several online programs offer more flexible admissions criteria, making it easier for motivated candidates to start their journey.

If you’re aiming for a fast track, consider enrolling in an accelerated computer science degree online. These programs let you earn your degree more quickly, launching your tech career sooner.

Computer science graduates often work in expanding areas such as environmental technology. With advancements in data analysis and sustainable solutions, there are also a variety of high-paying jobs with environmental science degree backgrounds.

For those drawn to engineering, you can combine science and technology through an online environmental engineering degree science and engineering. This route supports careers focused on designing innovative environmental solutions.

Best Scientists Citing Kai Li

Trending Scientists

Recently Published Articles