World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
12706
World Ranking
7039
National Ranking
3089

Martin J. Strauss 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 Martin J. Strauss 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: 105 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.

Martin J. Strauss 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 Martin J. Strauss 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Martin J. Strauss is a researcher affiliated with the University of Michigan-Ann Arbor in the United States. Their work primarily spans the domain of computer science, with a notable focus on signal processing and related subfields.

The researcher has contributed to areas encompassing speech and audio processing, music and audio processing, and hearing loss and rehabilitation. Their expertise also extends to advanced adaptive filtering techniques, ethics and social impacts of artificial intelligence, auction theory and applications, and privacy-preserving technologies in data.

Their recent scholarly output includes publications in various venues, most prominently arXiv (Cornell University) and the Leibniz-Zentrum für Informatik (Schloss Dagstuhl). The recent papers authored or co-authored by Martin J. Strauss include:

  • A Hands-on Comparison of DNNs for Dialog Separation Using Transfer Learning from Music Source Separation, 2021, arXiv (Cornell University)
  • Improved Normalizing Flow-Based Speech Enhancement using an All-pole Gammatone Filterbank for Conditional Input Representation, 2022, arXiv (Cornell University)
  • Predicting Preferred Dialogue-to-Background Loudness Difference in Dialogue-Separated Audio, 2023, arXiv (Cornell University)
  • FlowMAC: Conditional Flow Matching for Audio Coding at Low Bit Rates, 2024, arXiv (Cornell University)
  • Multiplicative Metric Fairness Under Composition, 2023, Leibniz-Zentrum für Informatik (Schloss Dagstuhl)

Martin J. Strauss frequently collaborates with several co-authors, including Bernd Edler, Matteo Torcoli, Amanda Bower, Sarah N. Kitchen, and Laura Niss. Among these, Bernd Edler and Matteo Torcoli are the most recurrent co-authors.

Their primary research encompasses the following fields of study:

  • Computer Science

Subfields of study include:

  • Signal Processing
  • Artificial Intelligence
  • Cognitive Neuroscience
  • Computational Mechanics
  • Safety Research

Key topics of their work are:

  • Speech and Audio Processing
  • Music and Audio Processing
  • Hearing Loss and Rehabilitation
  • Advanced Adaptive Filtering Techniques
  • Ethics and Social Impacts of AI
  • Auction Theory and Applications
  • Privacy-Preserving Technologies in Data

Best Publications

  • Divertible protocols and atomic proxy cryptography

    Matt Blaze;Gerrit Bleumer;Martin Strauss

  • Algorithms for simultaneous sparse approximation: part I: Greedy pursuit

    Joel A. Tropp;Anna C. Gilbert;Martin J. Strauss

  • Surfing Wavelets on Streams: One-Pass Summaries for Approximate Aggregate Queries

    Anna C. Gilbert;Yannis Kotidis;S. Muthukrishnan;Martin Strauss

  • Referee: trust management for Web applications

    Yang-Hua Chu;Joan Feigenbaum;Brian LaMacchia;Paul Resnick

  • Combining geometry and combinatorics: A unified approach to sparse signal recovery

    R. Berinde;A.C. Gilbert;P. Indyk;H. Karloff

  • Compliance Checking in the PolicyMaker Trust Management System

    Matt Blaze;Joan Feigenbaum;Martin Strauss

  • Simultaneous sparse approximation via greedy pursuit

    J.A. Tropp;A.C. Gilbert;M.J. Strauss

  • Near-optimal sparse fourier representations via sampling

    A. C. Gilbert;S. Guha;P. Indyk;S. Muthukrishnan

  • Fast, small-space algorithms for approximate histogram maintenance

    Anna C. Gilbert;Sudipto Guha;Piotr Indyk;Yannis Kotidis

  • One sketch for all: fast algorithms for compressed sensing

    A. C. Gilbert;M. J. Strauss;J. A. Tropp;R. Vershynin

  • An Approximate L 1 -Difference Algorithm for Massive Data Streams

    Joan Feigenbaum;Sampath Kannan;Martin J. Strauss;Mahesh Viswanathan

  • Random Sampling for Analog-to-Information Conversion of Wideband Signals

    J. Laska;S. Kirolos;Y. Massoud;R. Baraniuk

  • Maintaining time-decaying stream aggregates

    Edith Cohen;Martin Strauss

  • Improved time bounds for near-optimal sparse Fourier representations

    A. C. Gilbert;S. Muthukrishnan;M. Strauss

  • An approximate L/sup 1/-difference algorithm for massive data streams

    J. Feigenbaum;S. Kannan;M. Strauss;M. Viswanathan

  • Approximation of functions over redundant dictionaries using coherence

    Anna C. Gilbert;S. Muthukrishnan;Martin J. Strauss

  • How to summarize the universe: dynamic maintenance of quantiles

    Anna C. Gilbert;Yannis Kotidis;S. Muthukrishnan;Martin J. Strauss

  • Networks of strong ties

    Xiaolin Shi;Lada A. Adamic;Martin J. Strauss

  • One-pass wavelet decompositions of data streams

    A.C. Gilbert;Y. Kotidis;S. Muthukrishnan;M.J. Strauss

  • Algorithmic linear dimension reduction in the l_1 norm for sparse vectors

    Anna C. Gilbert;Martin J. Strauss;Joel A. Tropp;Roman Vershynin

  • An approximate Lp-difference algorithm for massive data streams

    J. H. Fong;M. J. Strauss

Frequent Co-Authors

Anna C. Gilbert
Anna C. Gilbert Yale University
Joan Feigenbaum
Joan Feigenbaum Yale University
s muthukrishnan
s muthukrishnan Rutgers, The State University of New Jersey
Ely Porat
Ely Porat Bar-Ilan University
Joel A. Tropp
Joel A. Tropp California Institute of Technology
Rebecca N. Wright
Rebecca N. Wright Barnard College
Sampath Kannan
Sampath Kannan University of Pennsylvania
Yuval Ishai
Yuval Ishai Technion – Israel Institute of Technology
Richard G. Baraniuk
Richard G. Baraniuk Rice University

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