World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
82
Citations
34866
World Ranking
943
National Ranking
516

Mehryar Mohri 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 Mehryar Mohri 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: 315 publications — 76th percentile

76% of scientists in this discipline score the same or lower.

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

Mehryar Mohri 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 Mehryar Mohri 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: 82 D-Index — 94th percentile

94% of scientists in this discipline score the same or lower.

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

Overview

Mehryar Mohri is affiliated with Google in the United States and has a substantial body of research primarily in the field of Computer Science. Their work spans multiple subfields including Artificial Intelligence, Management Science and Operations Research, Computer Networks and Communications, Computer Vision and Pattern Recognition, and Electrical and Electronic Engineering.

The research topics covered by Mehryar Mohri encompass areas such as Machine Learning and Algorithms, Advanced Bandit Algorithms Research, Domain Adaptation and Few-Shot Learning, Adversarial Robustness in Machine Learning, Machine Learning and Data Classification, Reinforcement Learning in Robotics, and Privacy-Preserving Technologies in Data.

Recent publications by Mehryar Mohri include the following papers:

  • Advances and Open Problems in Federated Learning, 2020, published in Foundations and Trends® in Machine Learning
  • Three Approaches for Personalization with Applications to Federated Learning, 2020, arXiv (Cornell University)
  • Cross-Entropy Loss Functions: Theoretical Analysis and Applications, 2023, arXiv (Cornell University)
  • A Field Guide to Federated Optimization, 2021, arXiv (Cornell University)
  • Mime: Mimicking Centralized Stochastic Algorithms in Federated Learning, 2020, arXiv (Cornell University)

Mehryar Mohri has collaborated frequently with several researchers, including Yutao Zhong, Pranjal Awasthi, Anqi Mao, Corinna Cortes, and Yishay Mansour. These collaborations have contributed to a consistent output of research, particularly reflected in multiple publications on arXiv (Cornell University).

Their frequent publication venues emphasize their connection to both preprint and peer-reviewed outlets, with a strong presence on arXiv (Cornell University), where they have 51 publications. Other venues include the Annals of Mathematics and Artificial Intelligence with 5 publications, Foundations and Trends® in Machine Learning, and the Journal of Global Optimization.

Best Publications

  • Advances and Open Problems in Federated Learning

    Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

  • Foundations of Machine Learning

    Mehryar Mohri;Afshin Rostamizadeh;Afshin Rostamizadeh;Ameet Talwalkar;Ameet Talwalkar

  • Finite-state transducers in language and speech processing

    Mehryar Mohri

  • Weighted finite-state transducers in speech recognition

    Mehryar Mohri;Fernando Pereira;Michael Riley

  • Advances and open problems in federated learning

    Peter Kairouz;H. Brendan McMahan;Brendan Avent;Aurélien Bellet

  • SCAFFOLD: Stochastic Controlled Averaging for Federated Learning

    Sai Praneeth Reddy Karimireddy;Satyen Kale;Mehryar Mohri;Sashank Jakkam Reddi

  • OpenFst: a general and efficient weighted finite-state transducer library

    Cyril Allauzen;Michael Riley;Johan Schalkwyk;Wojciech Skut

  • AUC Optimization vs. Error Rate Minimization

    Corinna Cortes;Mehryar Mohri

  • Multi-armed bandit algorithms and empirical evaluation

    Joannès Vermorel;Mehryar Mohri

  • Domain adaptation: Learning bounds and algorithms

    Yishay Mansour;Mehryar Mohri;Afshin Rostamizadeh

  • Algorithms for learning kernels based on centered alignment

    Corinna Cortes;Mehryar Mohri;Afshin Rostamizadeh

  • Domain Adaptation with Multiple Sources

    Yishay Mansour;Mehryar Mohri;Afshin Rostamizadeh

  • Agnostic federated learning

    Mehryar Mohri;Gary Sivek;Ananda Theertha Suresh

  • L 2 regularization for learning kernels

    Corinna Cortes;Mehryar Mohri;Afshin Rostamizadeh

  • Speech Recognition with Weighted Finite-State Transducers

    Mehryar Mohri;Fernando C. N. Pereira;Michael Riley

  • Semiring frameworks and algorithms for shortest-distance problems

    Mehryar Mohri

  • Sample Selection Bias Correction Theory

    Corinna Cortes;Mehryar Mohri;Michael Riley;Afshin Rostamizadeh

  • Sampling methods for the Nyström method

    Sanjiv Kumar;Mehryar Mohri;Ameet Talwalkar

  • Methods and Apparatus for Rapid Acoustic Unit Selection From a Large Speech Corpus

    Mark Charles Beutnagel;Mehryar Mohri;Michael Dennis Riley

  • Three Approaches for Personalization with Applications to Federated Learning.

    Yishay Mansour;Mehryar Mohri;Jae Ro;Ananda Theertha Suresh

Frequent Co-Authors

Corinna Cortes
Corinna Cortes Google (United States)
Michael Riley
Michael Riley Google (United States)
Afshin Rostamizadeh
Afshin Rostamizadeh Google (United States)
Ameet Talwalkar
Ameet Talwalkar Carnegie Mellon University
Satyen Kale
Satyen Kale Google (United States)
Yishay Mansour
Yishay Mansour Tel Aviv University
Fernando Pereira
Fernando Pereira Google (United States)
Karthik Sridharan
Karthik Sridharan Cornell University
Patrick Haffner
Patrick Haffner Interactions Corporation
Brian Roark
Brian Roark Google (United States)

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