World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
75
Citations
29149
World Ranking
665
National Ranking
297

Computer Science

D-Index
80
Citations
33506
World Ranking
1060
National Ranking
568

Daniel P. W. Ellis publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Daniel P. W. Ellis sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 379 publications — 72nd percentile

72% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 1,065 publications or more.

Daniel P. W. Ellis D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Daniel P. W. Ellis sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 75 D-Index — 90th percentile

90% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Research.com Recognitions

  • 2018 - IEEE Fellow For contributions to speech, audio, and music processing

Overview

Daniel P. W. Ellis is affiliated with Google in the United States and specializes in research within the field of Computer Science. Their work primarily focuses on Signal Processing, with additional contributions in Infectious Diseases, Computer Vision and Pattern Recognition, Speech and Hearing, and Music.

Their research covers several main topics including Music and Audio Processing, Speech and Audio Processing, Music Technology and Sound Studies, Noise Effects and Management, Diverse Musicological Studies, Hearing Loss and Rehabilitation, and Acoustic Wave Phenomena Research.

Daniel P. W. Ellis has published extensively in venues such as:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • IEEE Signal Processing Letters
  • Journal of Occupational and Environmental Hygiene

Recent papers include:

  • MuLan: A Joint Embedding of Music Audio and Natural Language, 2022, arXiv (Cornell University)
  • Into the Wild with AudioScope: Unsupervised Audio-Visual Separation of On-Screen Sounds, 2020, arXiv (Cornell University)
  • Addressing Missing Labels in Large-Scale Sound Event Recognition Using a Teacher-Student Framework With Loss Masking, 2020, IEEE Signal Processing Letters
  • Proceedings of the 6th Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE 2021), 2021, arXiv (Cornell University)
  • Description and analysis of novelties introduced in DCASE Task 4 2022 on the baseline system, 2022, arXiv (Cornell University)

Frequent co-authors in their research include:

  • Eduardo Fonseca
  • Aren Jansen
  • Manoj Plakal
  • Shawn Hershey
  • Frederic Font

Daniel P. W. Ellis was recognized as an IEEE Fellow in 2018 for contributions to speech, audio, and music processing.

Best Publications

  • librosa: Audio and Music Signal Analysis in Python

    Brian McFee;Colin Raffel;Dawen Liang;Daniel P.W. Ellis

  • Audio Set: An ontology and human-labeled dataset for audio events

    Jort F. Gemmeke;Daniel P. W. Ellis;Dylan Freedman;Aren Jansen

  • CNN architectures for large-scale audio classification

    Shawn Hershey;Sourish Chaudhuri;Daniel P. W. Ellis;Jort F. Gemmeke

  • THE MILLION SONG DATASET

    Thierry Bertin-Mahieux;Daniel P. W. Ellis;Brian Whitman;Paul Lamere

  • Speech and Audio Signal Processing: Processing and Perception of Speech and Music

    Ben Gold;Nelson Morgan;Dan Ellis

  • Tandem connectionist feature extraction for conventional HMM systems

    H. Hermansky;D.P.W. Ellis;S. Sharma

  • The ICSI Meeting Corpus

    A. Janin;D. Baron;J. Edwards;D. Ellis

  • Beat Tracking by Dynamic Programming

    Daniel P. W. Ellis

  • Identifying `Cover Songs' with Chroma Features and Dynamic Programming Beat Tracking

    D. P. W. Ellis;G. E. Poliner

  • Prediction-driven computational auditory scene analysis

    Daniel P. W. Ellis;Barry L. Vercoe

  • A Large-Scale Evaluation of Acoustic and Subjective Music-Similarity Measures

    Adam Berenzweig;Beth Logan;Daniel P. W. Ellis;Brian P. W. Whitman;Brian P. W. Whitman

  • MIR_EVAL: A Transparent Implementation of Common MIR Metrics.

    Colin Raffel;Brian McFee;Eric J. Humphrey;Justin Salamon

  • Chord Segmentation and Recognition using EM-Trained Hidden Markov Models

    Alexander Sheh;Daniel P. W. Ellis

  • Song-Level Features and Support Vector Machines for Music Classification

    Michael I. Mandel;Daniel P. W. Ellis

  • Consumer video understanding: a benchmark database and an evaluation of human and machine performance

    Yu-Gang Jiang;Guangnan Ye;Shih-Fu Chang;Daniel Ellis

  • Signal Processing for Music Analysis

    M. Muller;D. P. W. Ellis;A. Klapuri;G. Richard

  • Model-Based Expectation-Maximization Source Separation and Localization

    M.I. Mandel;R.J. Weiss;D. Ellis

  • A discriminative model for polyphonic piano transcription

    Graham E. Poliner;Daniel P. W. Ellis

  • Melody Extraction from Polyphonic Music Signals: Approaches, applications, and challenges

    Justin Salamon;Emilia Gomez;Daniel P. W. Ellis;Gael Richard

  • Melody Transcription From Music Audio: Approaches and Evaluation

    G.E. Poliner;D.P.W. Ellis;A.F. Ehmann;E. Gomez

  • Speech and Audio Signal Processing

    Simon King;Dan Ellis;Nelson Morgan

  • 8. Pattern Classification

    Unknown

Frequent Co-Authors

Nelson Morgan
Nelson Morgan International Computer Science Institute
Aren Jansen
Aren Jansen Google (United States)
Shih-Fu Chang
Shih-Fu Chang Columbia University
Hynek Hermansky
Hynek Hermansky Johns Hopkins University
Colin Raffel
Colin Raffel University of Toronto
Xavier Serra
Xavier Serra Pompeu Fabra University
Alexander C. Loui
Alexander C. Loui Rochester Institute of Technology
Martin Cooke
Martin Cooke Ikerbasque
Malcolm Slaney
Malcolm Slaney Stanford University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring Computer Science in the USA opens doors to numerous related online degrees and flexible career options. Many students consider expanding their knowledge in fields like engineering, physics, or data analytics, all through accessible virtual programs.

For example, those interested in physics can explore online physics degrees that offer foundational knowledge and diverse career possibilities. If you're leaning toward data, the data science learning path equips students with analytical and programming skills in high demand by employers.

Engineering-minded students should look at the top online electrical engineering schools for rigorous programs that deliver real-world applications in technology, power systems, and electronics.

Finally, for those seeking quicker entry or advancement, consider pursuing easy licenses and certifications to get—these credentials often help boost career prospects and salary potential without a long time investment.

Best Scientists Citing Daniel P. W. Ellis

Trending Scientists

Recently Published Articles