World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
32
Citations
5102
World Ranking
13065
National Ranking
5261

Nihar B. Shah 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 Nihar B. Shah 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: 152 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.

Nihar B. Shah 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 Nihar B. Shah 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: 32 D-Index — 10th percentile

10% of scientists in this discipline score the same or lower.

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

Overview

Nihar B. Shah is affiliated with Carnegie Mellon University in the United States. Their primary field of study is Computer Science, with a focus spanning several subfields including Artificial Intelligence, Information Systems, Management Science and Operations Research, Computer Science Applications, and Economics and Econometrics.

Their research topics include:

  • Expert finding and Q&A systems
  • Mobile Crowdsensing and Crowdsourcing
  • Topic Modeling
  • Auction Theory and Applications
  • Privacy-Preserving Technologies in Data
  • Software Engineering Research
  • Game Theory and Voting Systems

Recent papers authored or co-authored by Nihar B. Shah cover a range of subjects in their areas of expertise. Notable publications include:

  • "Some Simple Economics of Stablecoins" (2022) in Annual Review of Financial Economics
  • "Challenges, experiments, and computational solutions in peer review" (2022) in Communications of the ACM
  • "A Permutation-Based Model for Crowd Labeling: Optimal Estimation and Robustness" (2020) in IEEE Transactions on Information Theory
  • "Approval Voting and Incentives in Crowdsourcing" (2020) in ACM Transactions on Economics and Computation
  • "Uncovering Latent Biases in Text: Method and Application to Peer Review" (2021) in Proceedings of the AAAI Conference on Artificial Intelligence

Nihar B. Shah frequently collaborates with several co-authors, including:

  • Ivan Stelmakh
  • Hal Daumé
  • Charvi Rastogi
  • Steven Jecmen
  • Fei Fang

The scholar commonly publishes in several venues, with a significant number of papers appearing in:

  • arXiv (Cornell University)
  • PLoS ONE
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the AAAI Conference on Human Computation and Crowdsourcing
  • Communications of the ACM

Best Publications

  • Optimal Exact-Regenerating Codes for Distributed Storage at the MSR and MBR Points via a Product-Matrix Construction

    K. V. Rashmi;N. B. Shah;P. V. Kumar

  • Optimal Exact-Regenerating Codes for Distributed Storage at the MSR and MBR Points via a Product-Matrix Construction

    K. V. Rashmi;Nihar B. Shah;P. Vijay Kumar

  • Explicit construction of optimal exact regenerating codes for distributed storage

    K. V. Rashmi;Nihar B. Shah;P. Vijay Kumar;Kannan Ramchandran

  • Distributed Storage Codes With Repair-by-Transfer and Nonachievability of Interior Points on the Storage-Bandwidth Tradeoff

    N. B. Shah;K. V. Rashmi;P. Vijay Kumar;K. Ramchandran

  • A "hitchhiker's" guide to fast and efficient data reconstruction in erasure-coded data centers

    K.V. Rashmi;Nihar B. Shah;Dikang Gu;Hairong Kuang

  • A solution to the network challenges of data recovery in erasure-coded distributed storage systems: a study on the Facebook warehouse cluster

    K. V. Rashmi;Nihar B. Shah;Dikang Gu;Hairong Kuang

  • Interference Alignment in Regenerating Codes for Distributed Storage: Necessity and Code Constructions

    N. B. Shah;K. V. Rashmi;P. V. Kumar;K. Ramchandran

  • A "hitchhiker's" guide to fast and efficient data reconstruction in erasure-coded data centers

    Unknown

  • One Extra Bit of Download Ensures Perfectly Private Information Retrieval

    Nihar B. Shah;K. V. Rashmi;Kannan Ramchandran

  • When Do Redundant Requests Reduce Latency

    Nihar B. Shah;Kangwook Lee;Kannan Ramchandran

  • Distributed Storage Codes with Repair-by-Transfer and Non-achievability of Interior Points on the Storage-Bandwidth Tradeoff

    Nihar B. Shah;K. V. Rashmi;P. Vijay Kumar;Kannan Ramchandran

  • Interference Alignment in Regenerating Codes for Distributed Storage: Necessity and Code Constructions

    Nihar B. Shah;K. V. Rashmi;P. Vijay Kumar;Kannan Ramchandran

  • Simple, Robust and Optimal Ranking from Pairwise Comparisons

    Nihar B. Shah;Martin J. Wainwright

  • Having your cake and eating it too: jointly optimal erasure codes for I/O, storage and network-bandwidth

    K. V. Rashmi;Preetum Nakkiran;Jingyan Wang;Nihar B. Shah

  • Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues

    Nihar B. Shah;Sivaraman Balakrishnan;Adityanand Guntuboyina;Martin J. Wainwright

  • Estimation from pairwise comparisons: sharp minimax bounds with topology dependence

    Nihar B. Shah;Sivaraman Balakrishnan;Joseph Bradley;Abhay Parekh

  • Information-Theoretically Secure Regenerating Codes for Distributed Storage

    Nihar B. Shah;K. V. Rashmi;P. Vijay Kumar

  • A Piggybacking Design Framework for Read-and Download-Efficient Distributed Storage Codes

    K. V. Rashmi;Nihar B. Shah;Kannan Ramchandran

  • Explicit codes minimizing repair bandwidth for distributed storage

    Nihar B. Shah;K. V. Rashmi;P. Vijay Kumar;Kannan Ramchandran

  • Double or nothing: multiplicative incentive mechanisms for crowdsourcing

    Nihar B. Shah;Dengyong Zhou

  • Regenerating codes for errors and erasures in distributed storage

    K. V. Rashmi;Nihar B. Shah;Kannan Ramchandran;P. Vijay Kumar

  • Double or nothing: multiplicative incentive mechanisms for Crowdsourcing

    Nihar B. Shah;Dengyong Zhou

  • A Solution to the Network Challenges of Data Recovery in Erasure-coded Distributed Storage Systems: A Study on the Facebook Warehouse Cluster

    K. V. Rashmi;Nihar B. Shah;Dikang Gu;Hairong Kuang

  • Regularized Minimax Conditional Entropy for Crowdsourcing

    Dengyong Zhou;Qiang Liu;John C. Platt;Christopher Meek

  • When do redundant requests reduce latency

    Nihar B. Shah;Kangwook Lee;Kannan Ramchandran

  • Overcoming Calibration Problems in Pattern Labeling with Pairwise Ratings: Application to Personality Traits

    Baiyu Chen;Sergio Escalera;Isabelle Guyon;Víctor Ponce-López;Víctor Ponce-López

  • Simple, Robust and Optimal Ranking from Pairwise Comparisons

    Nihar B. Shah;Martin J. Wainwright

Frequent Co-Authors

Kannan Ramchandran
Kannan Ramchandran University of California, Berkeley
P. Vijay Kumar
P. Vijay Kumar Indian Institute of Science
Aarti Singh
Aarti Singh Carnegie Mellon University
Dengyong Zhou
Dengyong Zhou Google (United States)
Hal Daumé
Hal Daumé University of Maryland, College Park
R. Ravi
R. Ravi Carnegie Mellon University
P.V. Kumar
P.V. Kumar Indian Institute of Science
Ariel D. Procaccia
Ariel D. Procaccia Harvard University
Vincent Conitzer
Vincent Conitzer Carnegie Mellon University

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