World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
13804
World Ranking
5510
National Ranking
2515

Rina Panigrahy 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 Rina Panigrahy 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: 153 publications — 28th percentile

28% of scientists in this discipline score the same or lower.

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

Rina Panigrahy 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 Rina Panigrahy 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: 50 D-Index — 62nd percentile

62% of scientists in this discipline score the same or lower.

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

Overview

Rina Panigrahy is affiliated with Google in the United States and works primarily within the field of Computer Science. Their research production includes a significant focus on Artificial Intelligence, Computer Vision and Pattern Recognition, as well as Signal Processing and Computational Mechanics.

Their work spans a variety of specialized topics including Domain Adaptation and Few-Shot Learning, Speech Recognition and Synthesis, Topic Modeling, Advanced Image and Video Retrieval Techniques, Speech and Audio Processing, Music Technology and Sound Studies, and Algorithms and Data Compression.

Rina Panigrahy has published extensively with a notable presence on arXiv (Cornell University) and contributions to Interspeech 2022, Leibniz-Zentrum für Informatik (Schloss Dagstuhl), and the Journal of Molecular Liquids. The following are selected recent papers authored by or involving Panigrahy:

  • A Unified Cascaded Encoder ASR Model for Dynamic Model Sizes (2022), Interspeech 2022
  • Maximum Coverage in Random-Arrival Streams (2023), Leibniz-Zentrum für Informatik (Schloss Dagstuhl)
  • One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks (2021), arXiv (Cornell University)
  • For Manifold Learning, Deep Neural Networks can be Locality Sensitive Hash Functions (2021), arXiv (Cornell University)
  • Provable Hierarchical Lifelong Learning with a Sketch-based Modular Architecture (2021), arXiv (Cornell University)

Frequent collaborators in Panigrahy's research include Nishanth Dikkala, Xin Wang, Atish Agarwala, Abhimanyu Das, and Brendan Juba. These partnerships have contributed to multiple publications focusing on various intersections of machine learning and neural networks.

The main fields of study identified in Panigrahy's work are:

  • Computer Science

Subfields of study represented in their research are:

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Computational Mechanics
  • Materials Chemistry

The primary topics of research encompass:

  • Domain Adaptation and Few-Shot Learning
  • Speech Recognition and Synthesis
  • Topic Modeling
  • Advanced Image and Video Retrieval Techniques
  • Speech and Audio Processing
  • Music Technology and Sound Studies
  • Algorithms and Data Compression

Best Publications

  • Consistent hashing and random trees: distributed caching protocols for relieving hot spots on the World Wide Web

    David Karger;Eric Lehman;Tom Leighton;Rina Panigrahy

  • Design tradeoffs for SSD performance

    Nitin Agrawal;Vijayan Prabhakaran;Ted Wobber;John D. Davis

  • Spamming botnets: signatures and characteristics

    Yinglian Xie;Fang Yu;Kannan Achan;Rina Panigrahy

  • Achieving anonymity via clustering

    Gagan Aggarwal;Rina Panigrahy;Tomás Feder;Dilys Thomas

  • An improved construction for counting bloom filters

    Flavio Bonomi;Michael Mitzenmacher;Rina Panigrahy;Sushil Singh

  • The smallest grammar problem

    M. Charikar;E. Lehman;Ding Liu;R. Panigrahy

  • Anonymizing tables

    Gagan Aggarwal;Tomás Feder;Krishnaram Kenthapadi;Rajeev Motwani

  • Better streaming algorithms for clustering problems

    Moses Charikar;Liadan O'Callaghan;Rina Panigrahy

  • Achieving anonymity via clustering

    Gagan Aggarwal;Tomás Feder;Krishnaram Kenthapadi;Samir Khuller

  • Approximation Algorithms for k-Anonymity

    Gagan Aggarwal;Tomas Feder;Krishnaram Kenthapadi;Rajeev Motwani

  • Estimating PageRank on graph streams

    Atish Das Sarma;Sreenivas Gollapudi;Rina Panigrahy

  • Entropy based nearest neighbor search in high dimensions

    Rina Panigrahy

  • Beyond bloom filters: from approximate membership checks to approximate state machines

    Flavio Bonomi;Michael Mitzenmacher;Rina Panigrah;Sushil Singh

  • Heuristics for Vector Bin Packing

    Rina Panigrahy;Kunal Talwar;Lincoln Uyeda;Udi Wieder

  • Method for providing social network recommended content

    Harrington Timothy;Shenoy Rajesh;Najork Marc;Panigrahy Rina

  • A sketch-based distance oracle for web-scale graphs

    Atish Das Sarma;Sreenivas Gollapudi;Marc Najork;Rina Panigrahy

  • Learning Polynomials with Neural Networks

    Alexandr Andoni;Rina Panigrahy;Gregory Valiant;Li Zhang

  • Validating Heuristics for Virtual Machines Consolidation

    Sangmin Lee;Rina Panigrahy;Vijayan Prabhakaran;Venugopalan Ramasubramanian

  • Reducing TCAM power consumption and increasing throughput

    R. Panigrahy;S. Sharma

  • Clustering to minimize the sum of cluster diameters

    Moses Charikar;Rina Panigrahy

  • Lower Bounds on Locality Sensitive Hashing

    Rajeev Motwani;Assaf Naor;Rina Panigrahy

Frequent Co-Authors

Rajeev Motwani
Rajeev Motwani Stanford University
Tomás Feder
Tomás Feder Stanford University
Marc Najork
Marc Najork Google (United States)
Kunal Talwar
Kunal Talwar Apple (United States)
Li Zhang
Li Zhang Google (United States)
Ravi Kumar
Ravi Kumar Google (United States)
Moses Charikar
Moses Charikar Stanford University
Mehrdad Nourani
Mehrdad Nourani The University of Texas at Dallas
Alexandr Andoni
Alexandr Andoni Columbia University

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