World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
42
Citations
18295
World Ranking
8142
National Ranking
3487

Michael Collins 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 Michael Collins 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: 102 publications — 9th percentile

9% of scientists in this discipline score the same or lower.

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

Michael Collins 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 Michael Collins 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: 42 D-Index — 43rd percentile

43% of scientists in this discipline score the same or lower.

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

Overview

Michael Collins is a researcher affiliated with Google in the United States, whose work primarily spans the fields of Medicine and Neuroscience. Their publications focus on various specialized areas including Neurology, Pathology and Forensic Medicine, Genetics, Molecular Biology, and Pulmonary and Respiratory Medicine.

The main topics that characterize their research include:

  • Alcoholism and Thiamine Deficiency
  • Neuroinflammation and Neurodegeneration Mechanisms
  • Alcohol Consumption and Health Effects
  • Neurofibromatosis and Schwannoma Cases
  • Genetics and Neurodevelopmental Disorders
  • Ubiquitin and Proteasome Pathways
  • Cystic Fibrosis Research Advances

Michael Collins has contributed to multiple publication venues with notable frequency. These include:

  • Journal of Cystic Fibrosis
  • Journal of Consumer Affairs
  • Alcoholism Clinical and Experimental Research
  • Journal of Clinical Investigation
  • Advances in Neurotoxicology

Selected recent papers by Michael Collins feature the following titles:

  • "Moderate blood alcohol and brain neurovulnerability: Selective depletion of calcium-independent phospholipase A2, omega-3 docosahexaenoic acid, and its synaptamide derivative as a potential harbinger of deficits in anti-inflammatory reserve," published in 2021 in Alcoholism Clinical and Experimental Research
  • "A haploinsufficiency restoration strategy corrects neurobehavioral deficits in Nf1+/- mice," 2025, Journal of Clinical Investigation
  • "510: Humidity and drying time affect dispersion of bacteria from disposable home nebulizers," 2021, Journal of Cystic Fibrosis
  • "Issue Information," 2021, Journal of Consumer Affairs
  • "Issue Information," 2022, Journal of Consumer Affairs

Their collaborative work includes frequent co-authorship with several researchers, such as:

  • Julie Aitken Harris
  • Ronald Paul Hill
  • Natalie Ross Adkins
  • Kathryn J. Aikin
  • Craig Andrews

Best Publications

  • Discriminative training methods for hidden Markov models: theory and experiments with perceptron algorithms

    Michael Collins

  • Head-Driven Statistical Models for Natural Language Parsing

    Michael Collins

  • Natural Questions: A Benchmark for Question Answering Research

    Tom Kwiatkowski;Jennimaria Palomaki;Olivia Redfield;Michael Collins

  • Unsupervised Models for Named Entity Classification

    Michael Collins;Yoram Singer

  • Learning to map sentences to logical form: structured classification with probabilistic categorial grammars

    Luke S. Zettlemoyer;Michael Collins

  • Convolution Kernels for Natural Language

    Michael Collins;Nigel Duffy

  • Hidden Conditional Random Fields

    A. Quattoni;S. Wang;L.-P. Morency;M. Collins

  • Three Generative, Lexicalised Models for Statistical Parsing

    Michael Collins

  • Logistic Regression, AdaBoost and Bregman Distances

    Michael Collins;Robert E. Schapire;Yoram Singer

  • Discriminative Reranking for Natural Language Parsing

    Michael Collins;Terry Koo

  • A New Statistical Parser Based on Bigram Lexical Dependencies

    Michael John Collins

  • Discriminative Reranking for Natural Language Parsing

    Michael Collins

  • Clause Restructuring for Statistical Machine Translation

    Michael Collins;Philipp Koehn;Ivona Kucerova

  • New Ranking Algorithms for Parsing and Tagging: Kernels over Discrete Structures, and the Voted Perceptron

    Michael Collins;Nigel Duffy

  • Globally Normalized Transition-Based Neural Networks

    Daniel Andor;Chris Alberti;David Weiss;Aliaksei Severyn

  • A Generalization of Principal Components Analysis to the Exponential Family

    Michael Collins;S. Dasgupta;Robert E Schapire

  • Simple Semi-supervised Dependency Parsing

    Terry Koo;Xavier Carreras;Michael Collins

  • BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

    Christopher Clark;Kenton Lee;Ming-Wei Chang;Tom Kwiatkowski

  • Conditional Random Fields for Object Recognition

    Ariadna Quattoni;Michael Collins;Trevor Darrell

  • Incremental Parsing with the Perceptron Algorithm

    Michael Collins;Brian Roark

  • TyDi QA: A Benchmark for Information-Seeking Question Answering in Typologically Diverse Languages

    Jonathan H. Clark;Eunsol Choi;Michael Collins;Dan Garrette

  • Ranking Algorithms for Named Entity Extraction: Boosting and the VotedPerceptron

    Michael Collins

  • Transfer learning for image classification with sparse prototype representations

    A. Quattoni;M. Collins;T. Darrell

  • A Statistical Parser for Czech

    Michael Collins;Jan Hajic;Lance Ramshaw;Christoph Tillmann

  • Efficient Third-Order Dependency Parsers

    Terry Koo;Michael Collins

  • Prepositional Phrase Attachment Through a Backed-off Model

    Michael Collins;James Brooks

  • Structured Training for Neural Network Transition-Based Parsing

    David Weiss;Chris Alberti;Michael Collins;Slav Petrov

  • Synthetic QA Corpora Generation with Roundtrip Consistency

    Chris Alberti;Daniel Andor;Emily Pitler;Jacob Devlin

  • Sparse, Dense, and Attentional Representations for Text Retrieval

    Yi Luan;Jacob Eisenstein;Kristina Toutanova;Michael Collins

  • Discriminative n-gram language modeling

    Brian Roark;Murat Saraclar;Michael Collins

  • An efficient projection for l1, ∞ regularization

    Ariadna Quattoni;Xavier Carreras;Michael Collins;Trevor Darrell

Frequent Co-Authors

Jeffrey W. Moses
Jeffrey W. Moses Columbia University Medical Center
Martin B. Leon
Martin B. Leon Columbia University Medical Center
Gregg W. Stone
Gregg W. Stone Icahn School of Medicine at Mount Sinai
Roxana Mehran
Roxana Mehran Icahn School of Medicine at Mount Sinai
Alexandra J. Lansky
Alexandra J. Lansky Yale University
George Dangas
George Dangas Icahn School of Medicine at Mount Sinai
Gary S. Mintz
Gary S. Mintz Columbia University Medical Center
Shay B. Cohen
Shay B. Cohen University of Edinburgh
Alexander M. Rush
Alexander M. Rush Cornell University
Trevor Darrell
Trevor Darrell University of California, Berkeley

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

As computer science continues to evolve, students are seeking flexible and efficient ways to launch their tech careers. Many prospective learners are exploring the fastest online degree options, which can help you enter the workforce sooner without compromising education quality.

For those drawn to the cutting edge of technology, there are now a range of the best online ai degree programs to consider. These programs offer rigorous training in artificial intelligence and machine learning, fields that are in high demand and poised for significant growth.

Choosing the right specialization matters. If you’re thinking ahead, review the best degrees for the future to ensure your qualifications remain relevant as the job market shifts.

Finally, for graduates looking to further their education online, there are a number of easy masters programs to get into. These can help you build on your skills without overwhelming admission requirements, making advanced study more accessible.

Best Scientists Citing Michael Collins

Trending Scientists

Recently Published Articles