World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
89
Citations
40546
World Ranking
637
National Ranking
339

Lyle H. Ungar 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 Lyle H. Ungar 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: 250 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: 560 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: 424 scientists 242–251 publications: 408 scientists 252–261 publications: 378 scientists 262–271 publications: 300 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: 408 publications — 88th percentile

88% of scientists in this discipline score the same or lower.

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

Lyle H. Ungar 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 Lyle H. Ungar sits on this spectrum.

30–31 D-Index: 879 scientists 32–33 D-Index: 984 scientists 34–35 D-Index: 918 scientists 36–37 D-Index: 990 scientists 38–39 D-Index: 969 scientists 40–41 D-Index: 907 scientists 42–43 D-Index: 821 scientists 44–45 D-Index: 765 scientists 46–47 D-Index: 689 scientists 48–49 D-Index: 543 scientists 50–51 D-Index: 543 scientists 52–53 D-Index: 517 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: 89 D-Index — 96th percentile

96% of scientists in this discipline score the same or lower.

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

Overview

Lyle H. Ungar is affiliated with the University of Pennsylvania in the United States. Their research primarily spans the field of Psychology, with a focus on several subfields including Artificial Intelligence, Social Psychology, Experimental and Cognitive Psychology, Applied Psychology, and Sociology and Political Science.

Their work explores a range of topics such as Mental Health via Writing, Mental Health Research Topics, Digital Mental Health Interventions, Machine Learning in Healthcare, Topic Modeling, Misinformation and Its Impacts, and Sentiment Analysis and Opinion Mining.

Ungar has contributed to numerous publication venues, with frequent appearances in:

  • arXiv (Cornell University)
  • bioRxiv (Cold Spring Harbor Laboratory)
  • Proceedings of the International AAAI Conference on Web and Social Media
  • Proceedings of the National Academy of Sciences
  • Scientific Reports

Some of their recent papers include:

  • "Megastudies improve the impact of applied behavioural science" (2021), published in Nature
  • "Characterizing Geographic Variation in Well-Being Using Tweets" (2021), published in Proceedings of the International AAAI Conference on Web and Social Media
  • "Estimating geographic subjective well-being from Twitter: A comparison of dictionary and data-driven language methods" (2020), published in Proceedings of the National Academy of Sciences
  • "Analyzing Personality through Social Media Profile Picture Choice" (2021), published in Proceedings of the International AAAI Conference on Web and Social Media
  • "The emotional and mental health impact of the murder of George Floyd on the US population" (2021), published in Proceedings of the National Academy of Sciences

Lyle H. Ungar collaborates frequently with a group of co-authors including Salvatore Giorgi, Sharath Chandra Guntuku, Brenda Curtis, Johannes C. Eichstaedt, and H. Andrew Schwartz.

Best Publications

  • Methods and metrics for cold-start recommendations

    Andrew I. Schein;Alexandrin Popescul;Lyle H. Ungar;David M. Pennock

  • Personality, Gender, and Age in the Language of Social Media: The Open-Vocabulary Approach

    H. Andrew Schwartz;Johannes C. Eichstaedt;Margaret L. Kern;Lukasz Dziurzynski

  • Efficient clustering of high-dimensional data sets with application to reference matching

    Andrew McCallum;Kamal Nigam;Lyle H. Ungar

  • A hybrid neural network‐first principles approach to process modeling

    Dimitris C. Psichogios;Lyle H. Ungar

  • Clustering Methods for Collaborative Filtering

    Lyle H. Ungar;Dean P. Foster

  • Twitter as a Tool for Health Research: A Systematic Review

    Lauren Sinnenberg;Alison M. Buttenheim;Kevin Padrez;Christina Mancheno

  • Detecting depression and mental illness on social media: an integrative review

    Sharath Chandra Guntuku;David B Yaden;Margaret L Kern;Lyle H Ungar

  • Facebook language predicts depression in medical records.

    Johannes C. Eichstaedt;Robert J. Smith;Raina M. Merchant;Lyle H. Ungar

  • Probabilistic Models for Unified Collaborative and Content-Based Recommendation in Sparse-Data Environments

    Alexandrin Popescul;Lyle H. Ungar;David M. Pennock;Steve Lawrence

  • Iterative Combinatorial Auctions: Theory and Practice

    David C. Parkes;Lyle H. Ungar

  • Iterative combinatorial auctions: achieving economic and computational efficiency

    David Christopher Parkes;Lyle H. Ungar

  • Active learning for logistic regression: an evaluation

    Andrew Ian Schein;Lyle H. Ungar

  • Statistical Relational Learning for Link Prediction

    Alexandrin Popescul;Lyle H. Ungar

  • Psychological Strategies for Winning a Geopolitical Forecasting Tournament

    Barbara Mellers;Lyle Ungar;Jonathan Baron;Jaime Ramos

  • EmoNet: Fine-Grained Emotion Detection with Gated Recurrent Neural Networks

    Muhammad Abdul-Mageed;Lyle H. Ungar

  • Using radial basis functions to approximate a function and its error bounds

    J.A. Leonard;M.A. Kramer;L.H. Ungar

  • Multi-View Learning of Word Embeddings via CCA

    Paramveer Dhillon;Dean P Foster;Lyle H. Ungar

  • Beyond Binary Labels: Political Ideology Prediction of Twitter Users

    Daniel Preoţiuc-Pietro;Ye Liu;Daniel Hopkins;Lyle Ungar

  • Direct and indirect model based control using artificial neural networks

    Dimitris C. Psichogios;Lyle H. Ungar

  • Characterizing geographic variation in well-being using tweets

    Hansen Andrew Schwartz;Johannes C. Eichstaedt;Margaret L. Kern;Lukasz Dziurzynski

  • Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining

    Tina Eliassi-Rad;Lyle Ungar;Mark Craven;Dimitrios Gunopulos

Frequent Co-Authors

H. Andrew Schwartz
H. Andrew Schwartz Stony Brook University
Johannes C. Eichstaedt
Johannes C. Eichstaedt Stanford University
Dean P. Foster
Dean P. Foster Amazon (United States)
Margaret L. Kern
Margaret L. Kern University of Melbourne
Barbara A. Mellers
Barbara A. Mellers University of Pennsylvania
Martin E. P. Seligman
Martin E. P. Seligman University of Pennsylvania
Philip E. Tetlock
Philip E. Tetlock University of Pennsylvania
David Stillwell
David Stillwell University of Cambridge
Maarten Sap
Maarten Sap Carnegie Mellon University
Michal Kosinski
Michal Kosinski Stanford University

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