World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
31
Citations
5781
World Ranking
13444
National Ranking
5376

Harsha V. Madhyastha 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 Harsha V. Madhyastha 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: 104 publications — 10th percentile

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

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

Harsha V. Madhyastha 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 Harsha V. Madhyastha 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: 31 D-Index — 6th percentile

6% of scientists in this discipline score the same or lower.

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

Overview

Harsha V. Madhyastha is affiliated with the University of Southern California in the United States. Their research spans the fields of Engineering and Computer Science, with a focus on subfields including Industrial and Manufacturing Engineering, Artificial Intelligence, Management of Technology and Innovation, Computer Vision and Pattern Recognition, and Electrical and Electronic Engineering.

The scientist has contributed to topics such as Privacy-Preserving Technologies in Data, Digital Transformation in Industry, Collaboration in Agile Enterprises, Product Development and Customization, Advanced Neural Network Applications, Ferroelectric and Negative Capacitance Devices, and Mobile Crowdsensing and Crowdsourcing.

Recent publications by Madhyastha include the following papers:

  • "Distributed manufacturing for and by the masses," 2021, published in Science
  • "Oort: Efficient Federated Learning via Guided Participant Selection," 2020, published in arXiv (Cornell University)
  • "FedScale: Benchmarking Model and System Performance of Federated Learning at Scale," 2021, published in arXiv (Cornell University)
  • "A Collaborative Process Parameter Recommender System for Fleets of Networked Manufacturing Machines -- with Application to 3D Printing," 2025, published in arXiv (Cornell University)

Their frequent co-authors include:

  • Chinedum E. Okwudire
  • Fan Lai
  • Xiangfeng Zhu
  • Mosharaf Chowdhury
  • Yinwei Dai

The venues where Madhyastha publishes most often are:

  • arXiv (Cornell University)
  • Science

Best Publications

  • iPlane: an information plane for distributed services

    Harsha V. Madhyastha;Tomas Isdal;Michael Piatek;Colin Dixon

  • Improving the reliability of internet paths with one-hop source routing

    Krishna P. Gummadi;Harsha V. Madhyastha;Steven D. Gribble;Henry M. Levy

  • FlowSense: monitoring network utilization with zero measurement cost

    Curtis Yu;Cristian Lumezanu;Yueping Zhang;Vishal Singh

  • Understanding website complexity: measurements, metrics, and implications

    Michael Butkiewicz;Harsha V. Madhyastha;Vyas Sekar

  • SPANStore: cost-effective geo-replicated storage spanning multiple cloud services

    Zhe Wu;Michael Butkiewicz;Dorian Perkins;Ethan Katz-Bassett

  • Moving beyond end-to-end path information to optimize CDN performance

    Rupa Krishnan;Harsha V. Madhyastha;Sridhar Srinivasan;Sushant Jain

  • Engineering Egress with Edge Fabric: Steering Oceans of Content to the World

    Brandon Schlinker;Hyojeong Kim;Timothy Cui;Ethan Katz-Bassett

  • Reverse traceroute

    Ethan Katz-Bassett;Harsha V. Madhyastha;Vijay Kumar Adhikari;Colin Scott

  • LASTor: a low-latency AS-aware tor client

    Masoud Akhoondi;Curtis Yu;Harsha V. Madhyastha

  • Studying black holes in the internet with Hubble

    Ethan Katz-Bassett;Harsha V. Madhyastha;John P. John;Arvind Krishnamurthy

  • LASTor: A Low-Latency AS-Aware Tor Client

    M. Akhoondi;C. Yu;H. V. Madhyastha

  • KLOTSKI: reprioritizing web content to improve user experience on mobile devices

    Michael Butkiewicz;Daimeng Wang;Zhe Wu;Harsha V. Madhyastha

  • iPlane Nano: path prediction for peer-to-peer applications

    Harsha V. Madhyastha;Ethan Katz-Bassett;Thomas Anderson;Arvind Krishnamurthy

  • A structural approach to latency prediction

    Harsha V. Madhyastha;Thomas Anderson;Arvind Krishnamurthy;Neil Spring

  • Efficient and scalable socware detection in online social networks

    Sazzadur Rahman;Ting-Kai Huang;Harsha V. Madhyastha;Michalis Faloutsos

  • LIFEGUARD: practical repair of persistent route failures

    Ethan Katz-Bassett;Colin Scott;David R. Choffnes;Ítalo Cunha

  • CosTLO: cost-effective redundancy for lower latency variance on cloud storage services

    Zhe Wu;Curtis Yu;Harsha V. Madhyastha

  • Software-Defined Latency Monitoring in Data Center Networks

    Curtis Yu;Cristian Lumezanu;Abhishek B. Sharma;Qiang Xu

  • Pitfalls for ISP-friendly P2P design.

    Michael Piatek;Harsha V. Madhyastha;John P. John;Arvind Krishnamurthy

  • TritonSort: a balanced large-scale sorting system

    Alexander Rasmussen;George Porter;Michael Conley;Harsha V. Madhyastha

  • Oort: Efficient Federated Learning via Guided Participant Selection

    Fan Lai;Xiangfeng Zhu;Harsha V. Madhyastha;Mosharaf Chowdhury

  • Computing while charging: building a distributed computing infrastructure using smartphones

    Mustafa Y. Arslan;Indrajeet Singh;Shailendra Singh;Harsha V. Madhyastha

  • Characterizing web page complexity and its impact

    Michael Butkiewicz;Harsha V. Madhyastha;Vyas Sekar

Frequent Co-Authors

Srikanth V. Krishnamurthy
Srikanth V. Krishnamurthy University of California, Riverside
Arvind Krishnamurthy
Arvind Krishnamurthy University of Washington
Thomas Anderson
Thomas Anderson University of Washington
Ethan Katz-Bassett
Ethan Katz-Bassett Columbia University
Michalis Faloutsos
Michalis Faloutsos University of California, Riverside
Mosharaf Chowdhury
Mosharaf Chowdhury University of Michigan–Ann Arbor
Amin Vahdat
Amin Vahdat Google (United States)
Arun Venkataramani
Arun Venkataramani University of Massachusetts Amherst
C. Siva Ram Murthy
C. Siva Ram Murthy Indian Institute of Technology Madras
Vyas Sekar
Vyas Sekar Carnegie Mellon University

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