World's Best Scientists 2026 revealed!
Marco Tagliasacchi

Marco Tagliasacchi

D-Index & Metrics

Computer Science

D-Index
43
Citations
8731
World Ranking
7923
National Ranking
147

Marco Tagliasacchi 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 Marco Tagliasacchi 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: 222 publications — 54th percentile

54% of scientists in this discipline score the same or lower.

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

Marco Tagliasacchi 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 Marco Tagliasacchi 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: 43 D-Index — 46th percentile

46% of scientists in this discipline score the same or lower.

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

Overview

Marco Tagliasacchi is a researcher affiliated with Google (Switzerland), based in Switzerland. Their primary field of study is Computer Science, with a strong focus on Signal Processing, Artificial Intelligence, and related subfields. They contribute actively to research areas including Speech Recognition and Synthesis, Speech and Audio Processing, Music and Audio Processing, and Natural Language Processing Techniques.

Their most frequent co-authors include Zalán Borsos, Neil Zeghidour, Matt Sharifi, Eugene Kharitonov, and Félix de Chaumont Quitry. These collaborations reflect a network concentrated in audio and speech technology research.

Marco Tagliasacchi has been published extensively in venues such as arXiv (Cornell University), IEEE Signal Processing Letters, Interspeech, IEEE/ACM Transactions on Audio Speech and Language Processing, and the Transactions of the Association for Computational Linguistics.

Recent papers by Marco Tagliasacchi include:

  • AudioLM: A Language Modeling Approach to Audio Generation, 2023, IEEE/ACM Transactions on Audio Speech and Language Processing
  • MuChoMusic dataset, 2024, arXiv (Cornell University)
  • Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision, 2023, Transactions of the Association for Computational Linguistics
  • Pre-Training Audio Representations With Self-Supervision, 2020, IEEE Signal Processing Letters
  • AudioPaLM: A Large Language Model That Can Speak and Listen, 2023, arXiv (Cornell University)

The topics covered in these publications emphasize speech and audio processing, as well as advances in machine learning techniques applied to audio generation and synthesis. These works illustrate involvement with cutting-edge studies in high-fidelity text-to-speech systems, self-supervised representation learning, and language modeling applied to audio data.

Best Publications

  • Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context

    Unknown

  • AudioLM: A Language Modeling Approach to Audio Generation

    Unknown

  • Scream and gunshot detection and localization for audio-surveillance systems

    G. Valenzise;L. Gerosa;M. Tagliasacchi;F. Antonacci

  • An overview on video forensics

    P. Bestagini;K. M. Fontani;S. Milani;M. Barni

  • Deep Convolutional Neural Networks for pedestrian detection

    D. Tomè;F. Monti;L. Baroffio;L. Bondi

  • An integrated system based on wireless sensor networks for patient monitoring, localization and tracking

    Alessandro Redondi;Marco Chirico;Luca Borsani;Matteo Cesana

  • Subjective assessment of H.264/AVC video sequences transmitted over a noisy channel

    F. De Simone;M. Naccari;M. Tagliasacchi;F. Dufaux

  • Local tampering detection in video sequences

    Paolo Bestagini;Simone Milani;Marco Tagliasacchi;Stefano Tubaro

  • A H.264/AVC video database for the evaluation of quality metrics

    F. De Simone;M. Tagliasacchi;M. Naccari;S. Tubaro

  • Scream and gunshot detection in noisy environments

    L. Gerosa;G. Valenzise;M. Tagliasacchi;F. Antonacci

  • Towards Learning a Universal Non-Semantic Representation of Speech.

    Joel Shor;Aren Jansen;Ronnie Maor;Oran Lang

  • Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision

    Unknown

  • Evaluation of low-complexity visual feature detectors and descriptors

    A. Canclini;M. Cesana;A. Redondi;M. Tagliasacchi

  • A visual sensor network for parking lot occupancy detection in Smart Cities

    Luca Baroffio;Luca Bondi;Matteo Cesana;Alessandro Enrico Redondi

  • No-Reference Video Quality Monitoring for H.264/AVC Coded Video

    M. Naccari;M. Tagliasacchi;S. Tubaro

  • Hash-Based Identification of Sparse Image Tampering

    M. Tagliasacchi;G. Valenzise;S. Tubaro

  • AudioPaLM: A Large Language Model That Can Speak and Listen

    Unknown

  • Countering JPEG anti-forensics

    G. Valenzise;V. Nobile;M. Tagliasacchi;S. Tubaro

  • Revealing the Traces of JPEG Compression Anti-Forensics

    G. Valenzise;M. Tagliasacchi;S. Tubaro

  • Compress-then-analyze vs. analyze-then-compress: Two paradigms for image analysis in visual sensor networks

    Alessandro Redondi;Luca Baroffio;Matteo Cesana;Marco Tagliasacchi

  • Top-k bounded diversification

    Piero Fraternali;Davide Martinenghi;Marco Tagliasacchi

  • Video codec identification

    P. Bestagini;A. Allam;S. Milani;M. Tagliasacchi

  • Ranking with uncertain scoring functions: semantics and sensitivity measures

    Mohamed A. Soliman;Ihab F. Ilyas;Davide Martinenghi;Marco Tagliasacchi

  • Discriminating multiple JPEG compression using first digit features

    Simone Milani;Marco Tagliasacchi;Stefano Tubaro

Frequent Co-Authors

Stefano Tubaro
Stefano Tubaro Polytechnic University of Milan
Matteo Cesana
Matteo Cesana Polytechnic University of Milan
Piero Fraternali
Piero Fraternali Polytechnic University of Milan
Augusto Sarti
Augusto Sarti Polytechnic University of Milan
Paolo Bestagini
Paolo Bestagini Polytechnic University of Milan
Stefano Ceri
Stefano Ceri Polytechnic University of Milan
Marco Brambilla
Marco Brambilla Polytechnic University of Milan
Pier Luigi Dragotti
Pier Luigi Dragotti Imperial College London
Ihab F. Ilyas
Ihab F. Ilyas University of Waterloo
Anderson Rocha
Anderson Rocha State University of Campinas

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