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Michael Kearns

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 79 1134 1098 603 581 227 27425

Michael Kearns publications per year

The chart shows the history of publications by Michael Kearns between 1987 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Michael Kearns published across 40 years, from 1987 to 2026, averaging 6.5 papers a year. Output peaked at 17 publications in 1994. 6 of the 258 publications appeared in the last two years.

No. of publications
5 10 15
Bar chart. Horizontal axis: year, 1987 to 2026. Vertical axis: number of publications, 0 to 17. Peak 17 publications in 1994. 1987: 2 publications 1988: 3 publications 1989: 4 publications 1990: 5 publications 1991: 5 publications 1992: 4 publications 1993: 6 publications 1994: 17 publications 1995: 7 publications 1996: 3 publications 1997: 3 publications 1998: 11 publications 1999: 6 publications 2000: 9 publications 2001: 5 publications 2002: 9 publications 2003: 5 publications 2004: 3 publications 2005: 6 publications 2006: 7 publications 2007: 5 publications 2008: 6 publications 2009: 5 publications 2010: 7 publications 2011: 11 publications 2012: 9 publications 2013: 5 publications 2014: 9 publications 2015: 5 publications 2016: 10 publications 2017: 7 publications 2018: 3 publications 2019: 10 publications 2020: 4 publications 2021: 8 publications 2022: 10 publications 2023: 8 publications 2024: 10 publications 2025: 5 publications 2026: 1 publication
1987 2026

258 publications in total across all disciplines

View publications per year as a table
Michael Kearns: publications per year, 1987 to 2026
Year Publications
1987 2
1988 3
1989 4
1990 5
1991 5
1992 4
1993 6
1994 17
1995 7
1996 3
1997 3
1998 11
1999 6
2000 9
2001 5
2002 9
2003 5
2004 3
2005 6
2006 7
2007 5
2008 6
2009 5
2010 7
2011 11
2012 9
2013 5
2014 9
2015 5
2016 10
2017 7
2018 3
2019 10
2020 4
2021 8
2022 10
2023 8
2024 10
2025 5
2026 1
Total 258
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Michael Kearns 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 Kearns sits on this spectrum.

No. of scientists
200 400 600
Bar chart with 97 bars. Horizontal axis: publications, 32–41 to 991+. Vertical axis: number of scientists, 0 to 609. Most scientists, 609, have 142–151 publications. The last bar groups every scientist with 991 publications or more. The highlighted bar, 222–231 publications, is where this scientist sits. 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
32–41 publications 991+

This scientist: 227 publications — 56th percentile

56% of scientists in this discipline score the same or lower.

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

View publications distribution as a table
Number of Computer Science scientists by publication count, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
Publications Scientists This scientist
32–41 7
42–51 22
52–61 82
62–71 134
72–81 249
82–91 324
92–101 421
102–111 420
112–121 497
122–131 544
132–141 555
142–151 609
152–161 559
162–171 534
172–181 556
182–191 583
192–201 519
202–211 508
212–221 490
222–231 437 227
232–241 423
242–251 408
252–261 377
262–271 301
272–281 335
282–291 320
292–301 293
302–311 250
312–321 238
322–331 206
332–341 209
342–351 208
352–361 162
362–371 176
372–381 127
382–391 158
392–401 128
402–411 104
412–421 94
422–431 99
432–441 83
442–451 108
452–461 73
462–471 77
472–481 69
482–491 84
492–501 62
502–511 54
512–521 57
522–531 51
532–541 51
542–551 32
552–561 38
562–571 28
572–581 43
582–591 33
592–601 41
602–611 32
612–621 28
622–631 25
632–641 27
642–651 17
652–661 20
662–671 17
672–681 15
682–691 14
692–701 21
702–711 13
712–721 12
722–731 19
732–741 14
742–751 12
752–761 10
762–771 10
772–781 11
782–791 10
792–801 11
802–811 8
812–821 8
822–831 7
832–841 11
842–851 10
852–861 5
862–871 9
872–881 4
882–891 6
892–901 3
902–911 6
912–921 3
922–931 2
932–941 2
942–951 2
952–961 3
962–971 3
972–981 3
982–990 5
991+ 100
Download as CSV

Michael Kearns 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 Kearns sits on this spectrum.

No. of scientists
200 400 600 800
Bar chart with 52 bars. Horizontal axis: D-Index, 30–31 to 131+. Vertical axis: number of scientists, 0 to 990. Most scientists, 990, have 36–37 D-Index. The last bar groups every scientist with 131 D-Index or more. The highlighted bar, 78–79 D-Index, is where this scientist sits. 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
30–31 D-Index 131+

This scientist: 79 D-Index — 92nd percentile

92% of scientists in this discipline score the same or lower.

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

View D-Index distribution as a table
Number of Computer Science scientists by D-index, Research.com 2026 ranking edition. Based on 14,188 ranked scientists.
D-Index Scientists This scientist
30–31 879
32–33 983
34–35 918
36–37 990
38–39 968
40–41 907
42–43 821
44–45 763
46–47 689
48–49 543
50–51 543
52–53 518
54–55 500
56–57 458
58–59 400
60–61 337
62–63 308
64–65 292
66–67 249
68–69 213
70–71 192
72–73 189
74–75 165
76–77 139
78–79 119 79
80–81 121
82–83 113
84–85 88
86–87 87
88–89 75
90–91 69
92–93 57
94–95 46
96–97 38
98–99 34
100–101 36
102–103 27
104–105 37
106–107 18
108–109 31
110–111 19
112–113 16
114–115 12
116–117 20
118–119 15
120–121 5
122–123 20
124–125 8
126–127 5
128–129 7
130 3
131+ 98
Download as CSV

Research.com Recognitions

  • 2014 - ACM Fellow For contributions to machine learning, artificial intelligence, and algorithmic game theory and computational social science.
  • 2012 - Fellow of the American Academy of Arts and Sciences
  • 2003 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to computational learning theory, to reinforcement learning and stochastic planning, to dialogue agents, and to the theory of multi-agent systems.

Overview

Michael Kearns is affiliated with the University of Pennsylvania in the United States and primarily focuses on research in computer science, with a specialization in artificial intelligence. Their work spans several subfields including safety research, sociology and political science, information systems, and epidemiology.

The scientist's recent publications illustrate a diverse engagement with topics related to algorithms, privacy, and ethics. Some notable papers include:

  • The Ethical Algorithm: The Science of Socially Aware Algorithm Design (2021, Perspectives on Science and Christian Faith)
  • Mixed Differential Privacy in Computer Vision (2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition)
  • Confidence-ranked reconstruction of census microdata from published statistics (2023, Proceedings of the National Academy of Sciences)
  • Ethical algorithm design (2020, ACM SIGecom Exchanges)
  • An Algorithmic Framework for Bias Bounties (2022, 2022 ACM Conference on Fairness, Accountability, and Transparency)

Frequent coauthors collaborating with Michael Kearns include Aaron Roth, Zhiwei Steven Wu, Emily Diana, Ira Globus-Harris, and Alessandro Achille. The collaboration with these researchers reflects interdisciplinary efforts in areas related to their main topics of study.

Michael Kearns publishes regularly in venues such as arXiv (Cornell University), Proceedings of the National Academy of Sciences, Leibniz-Zentrum für Informatik (Schloss Dagstuhl), the ACM Conference on Fairness, Accountability, and Transparency, and Perspectives on Science and Christian Faith.

Their research focuses on key topics within computer science including:

  • Privacy-preserving technologies in data
  • Stochastic gradient optimization techniques
  • Ethics and social impacts of artificial intelligence
  • Adversarial robustness in machine learning
  • Machine learning and data classification
  • Cryptography and data security
  • Criminal justice and corrections analysis

Over their career, Michael Kearns has received recognition such as the ACM Fellow award in 2014 for contributions to machine learning, artificial intelligence, algorithmic game theory, and computational social science. They were also named a Fellow of the American Academy of Arts and Sciences in 2012 and a Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) in 2003, highlighting contributions to computational learning theory, reinforcement learning, stochastic planning, dialogue agents, and multi-agent systems.

Best Publications

  • An Introduction to Computational Learning Theory

    Michael J. Kearns;Umesh V. Vazirani

  • Cryptographic limitations on learning Boolean formulae and finite automata

    Michael Kearns;Leslie Valiant

  • Efficient noise-tolerant learning from statistical queries

    Michael Kearns

  • Near-Optimal Reinforcement Learning in Polynomial Time

    Michael Kearns;Satinder Singh

  • A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes

    Michael Kearns;Yishay Mansour;Andrew Y. Ng

  • Algorithmic stability and sanity-check bounds for leave-one-out cross-validation

    Michael Kearns;Dana Ron

  • Learning in the presence of malicious errors

    Michael Kearns;Ming Li

  • Graphical models for game theory

    Michael J. Kearns;Michael L. Littman;Satinder P. Singh

  • Efficient distribution-free learning of probabilistic concepts

    Michael J. Kearns;Robert E. Schapire

  • Toward efficient agnostic learning

    Michael J. Kearns;Robert E. Schapire;Linda M. Sellie

  • On the Boosting Ability of Top-Down Decision Tree Learning Algorithms

    Michael Kearns;Yishay Mansour

  • On the Complexity of Teaching

    S.A. Goldman;M.J. Kearns

  • Optimizing dialogue management with reinforcement learning: experiments with the NJFun system

    Satinder Singh;Diane Litman;Michael Kearns;Marilyn Walker

  • Preventing Fairness Gerrymandering: Auditing and Learning for Subgroup Fairness

    Michael J. Kearns;Seth Neel;Aaron Roth;Zhiwei Steven Wu

  • Cryptographic Primitives Based on Hard Learning Problems

    Avrim Blum;Merrick L. Furst;Michael J. Kearns;Richard J. Lipton

  • On the learnability of Boolean formulae

    M. Kearns;M. Li;L. Pitt;L. Valiant

  • An Experimental Study of the Coloring Problem on Human Subject Networks

    Michael Kearns;Siddharth Suri;Nick Montfort

  • Nash convergence of gradient dynamics in general-sum games

    Satinder P. Singh;Michael J. Kearns;Yishay Mansour

  • Fairness in learning: classic and contextual bandits

    Matthew Joseph;Michael Kearns;Jamie Morgenstern;Aaron Roth

  • Near-Optimal Reinforcement Learning in Polynominal Time

    Michael J. Kearns;Satinder P. Singh

  • Proceedings of the 1997 conference on Advances in neural information processing systems 10

    Michael I. Jordan;Michael J. Kearns;Sara A. Solla

Frequent Co-Authors

Aaron Roth
Aaron Roth University of Pennsylvania
Yishay Mansour
Yishay Mansour Tel Aviv University
Satinder Singh
Satinder Singh DeepMind (United Kingdom)
Robert E. Schapire
Robert E. Schapire Microsoft (United States)
Sally A. Goldman
Sally A. Goldman Google
Umesh Vazirani
Umesh Vazirani University of California, Berkeley
Dana Ron
Dana Ron Tel Aviv University
Leslie G. Valiant
Leslie G. Valiant Harvard University
Andrew Y. Ng
Andrew Y. Ng Stanford University
David Haussler
David Haussler University of California, Santa Cruz

External Links

Wikipedia of Michael Kearns Personal website of Michael Kearns Google Scholar page

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Best Scientists Citing Michael Kearns

Rocco A. Servedio

Rocco A. Servedio

Columbia University

Publications: 105

Vitaly Feldman

Vitaly Feldman

Apple (United States)

Publications: 83

Avrim Blum

Avrim Blum

Toyota Technological Institute at Chicago

Publications: 71

Michael L. Littman

Michael L. Littman

Brown University

Publications: 67

Yishay Mansour

Yishay Mansour

Tel Aviv University

Publications: 67

Peter Stone

Peter Stone

The University of Texas at Austin

Publications: 60

Richard Nock

Richard Nock

Australian National University

Publications: 57

Aaron Roth

Aaron Roth

University of Pennsylvania

Publications: 53

Ilias Diakonikolas

Ilias Diakonikolas

University of Wisconsin–Madison

Publications: 51

Lihong Li

Lihong Li

Amazon (United States)

Publications: 50

Dan Roth

Dan Roth

University of Pennsylvania

Publications: 45

John Langford

John Langford

Microsoft (United States)

Publications: 43

Olivier Pietquin

Olivier Pietquin

Google (United States)

Publications: 43

Adam R. Klivans

Adam R. Klivans

The University of Texas at Austin

Publications: 42

Shie Mannor

Shie Mannor

Technion – Israel Institute of Technology

Publications: 42

Robert E. Schapire

Robert E. Schapire

Microsoft (United States)

Publications: 41

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