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Ed H. Chi

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 86 753 728 401 387 345 37802

Ed H. Chi publications per year

The chart shows the history of publications by Ed H. Chi between 1995 and 2021, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Ed H. Chi published across 27 years, from 1995 to 2021, averaging 11.8 papers a year. Output peaked at 27 publications in 2010. 46 of the 319 publications appeared in the last two years.

No. of publications
5 10 15 20 25
Bar chart. Horizontal axis: year, 1995 to 2021. Vertical axis: number of publications, 0 to 27. Peak 27 publications in 2010. 1995: 3 publications 1996: 1 publication 1997: 3 publications 1998: 2 publications 1999: 16 publications 2000: 13 publications 2001: 4 publications 2002: 22 publications 2003: 6 publications 2004: 5 publications 2005: 10 publications 2006: 11 publications 2007: 10 publications 2008: 17 publications 2009: 21 publications 2010: 27 publications 2011: 23 publications 2012: 14 publications 2013: 11 publications 2014: 5 publications 2015: 7 publications 2016: 6 publications 2017: 5 publications 2018: 13 publications 2019: 18 publications 2020: 27 publications 2021: 19 publications
1995 2021

319 publications in total across all disciplines

View publications per year as a table
Ed H. Chi: publications per year, 1995 to 2021
Year Publications
1995 3
1996 1
1997 3
1998 2
1999 16
2000 13
2001 4
2002 22
2003 6
2004 5
2005 10
2006 11
2007 10
2008 17
2009 21
2010 27
2011 23
2012 14
2013 11
2014 5
2015 7
2016 6
2017 5
2018 13
2019 18
2020 27
2021 19
Total 319
Download as CSV

Ed H. Chi publications per year - data summary

  • Ed H. Chi, a Computer Science scholar from Google (United States), has 319 publications recorded across 27 years, from 1995 to 2021.
  • The oldest publication on record dates to 1995 and the most recent to 2021.
  • The most productive years are 2010 and 2020, with 27 publications each.
  • The least productive year with any output is 1996, with 1 publication.
  • The rate of publication averages 11.8 papers per year over the whole span, or 11.8 per year counting only the 27 years with at least one publication.
  • The last 5 years on the chart (2017-2021) hold 82 publications, 26% of the career total.
  • Split into equal eras - 1995-2003: 70 publications (7.8 per year); 2004-2012: 138 publications (15.3 per year); 2013-2021: 111 publications (12.3 per year).
  • Comparing the opening and closing eras, the overall trend of publication is rising.

Ed H. Chi 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 Ed H. Chi 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, 342–351 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: 345 publications — 81st percentile

81% 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
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
342–351 208 345
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

Ed H. Chi publication distribution in Computer Science in 2026 - data summary

  • The chart plots the publication count of all 14,188 Computer Science scientists ranked by Research.com in 2026, grouped into 97 ranges running from 32–41 to 991+ publications.
  • Ed H. Chi, a Computer Science scholar from Google (United States), records 345 publications - the 81st percentile of the discipline.
  • 81% of ranked Computer Science scientists score the same or lower than Ed H. Chi, and about 19% score higher.
  • The median of the discipline falls in the 202–211 publications range, and Ed H. Chi ranks above the median.
  • The most crowded range is 142–151 publications, holding 609 scientists (4% of the field).
  • 70% of the field sits in the lowest quarter of the value range (up to 272–281 publications), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 991 publications or more, 100 scientists in all (<1% of the field).

Ed H. Chi 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 Ed H. Chi 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, 86–87 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: 86 D-Index — 95th percentile

95% 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
80–81 121
82–83 113
84–85 88
86–87 87 86
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

Ed H. Chi D-index placement in Computer Science in 2026 - data summary

  • The chart plots the discipline H-index (D-index) of all 14,188 Computer Science scientists ranked by Research.com in 2026, grouped into 52 ranges running from 30–31 to 131+ D-Index.
  • Ed H. Chi, a Computer Science scholar from Google (United States), records 86 D-Index - the 95th percentile of the discipline.
  • 95% of ranked Computer Science scientists score the same or lower than Ed H. Chi, and about 5% score higher.
  • The median of the discipline falls in the 44–45 D-Index range, and Ed H. Chi ranks above the median.
  • The most crowded range is 36–37 D-Index, holding 990 scientists (7% of the field).
  • 71% of the field sits in the lowest quarter of the value range (up to 54–55 D-Index), so the distribution is heavily right-skewed and high scores are rare.
  • The final bar has no upper bound: it groups every scientist with 131 D-Index or more, 98 scientists in all (<1% of the field).

Research.com Recognitions

  • 2014 - ACM Distinguished Member
  • 2013 - ACM Senior Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • World Wide Web
  • Law

Ed H. Chi mainly focuses on World Wide Web, Information retrieval, Cluster analysis, Human–computer interaction and Visualization. His research integrates issues of Information seeking, User modeling, Sensemaking and Internet privacy in his study of World Wide Web. His work deals with themes such as Information scent, Word and Reading, which intersect with Information retrieval.

Ed H. Chi focuses mostly in the field of Cluster analysis, narrowing it down to topics relating to Similarity and, in certain cases, Object. His biological study spans a wide range of topics, including Information visualization, Data visualization and Data science. Ed H. Chi has included themes like Social computing, Web design, Web development, Web-based simulation and Data Web in his Visualization study.

His most cited work include:

  • Crowdsourcing user studies with Mechanical Turk (1544 citations)
  • Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network (876 citations)
  • He says, she says: conflict and coordination in Wikipedia (464 citations)

What are the main themes of his work throughout his whole career to date?

Ed H. Chi mostly deals with World Wide Web, Information retrieval, Artificial intelligence, Recommender system and Machine learning. His World Wide Web research is multidisciplinary, incorporating elements of Information seeking, Internet privacy and Reading. His studies deal with areas such as Annotation, Set, Data mining and Information needs as well as Information retrieval.

His Data mining research is multidisciplinary, incorporating perspectives in Similarity and Cluster analysis. The Artificial intelligence study combines topics in areas such as Pattern recognition, Task and Natural language processing. As a member of one scientific family, he mostly works in the field of Recommender system, focusing on Human–computer interaction and, on occasion, User modeling.

He most often published in these fields:

  • World Wide Web (29.19%)
  • Information retrieval (23.91%)
  • Artificial intelligence (17.08%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (17.08%)
  • Recommender system (15.53%)
  • Machine learning (11.80%)

In recent papers he was focusing on the following fields of study:

His primary scientific interests are in Artificial intelligence, Recommender system, Machine learning, Artificial neural network and Ranking. His research investigates the link between Artificial intelligence and topics such as Task that cross with problems in Representation and Perspective. Recommender system is a subfield of Information retrieval that Ed H. Chi investigates.

His Information retrieval research is multidisciplinary, relying on both Transfer of learning and Task. His study on Regularization is often connected to Quality as part of broader study in Machine learning. The concepts of his Artificial neural network study are interwoven with issues in Ensemble forecasting and Encoding.

Between 2018 and 2021, his most popular works were:

  • Top-K Off-Policy Correction for a REINFORCE Recommender System (99 citations)
  • Fairness in Recommendation Ranking through Pairwise Comparisons (84 citations)
  • SageDB: A Learned Database System (74 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Machine learning
  • Law

Artificial intelligence, Machine learning, Recommender system, Ranking and Computation are his primary areas of study. His Artificial intelligence research incorporates elements of Domain and User experience design. His work in the fields of Machine learning, such as Artificial neural network, intersects with other areas such as Long range dependent and Dynamics.

His Recommender system study is concerned with the larger field of Information retrieval. His Computation study which covers Overhead that intersects with Theoretical computer science and Recurrent neural network. The various areas that Ed H. Chi examines in his Data science study include Contextual image classification and Product.

Best Publications

  • Self-Consistency Improves Chain of Thought Reasoning in Language Models

    Unknown

  • Crowdsourcing user studies with Mechanical Turk

    Aniket Kittur;Ed H. Chi;Bongwon Suh

  • Scaling Instruction-Finetuned Language Models

    Unknown

  • Emergent Abilities of Large Language Models

    Unknown

  • Want to be Retweeted? Large Scale Analytics on Factors Impacting Retweet in Twitter Network

    Bongwon Suh;Lichan Hong;Peter Pirolli;Ed H. Chi

  • Modeling Task Relationships in Multi-task Learning with Multi-gate Mixture-of-Experts

    Jiaqi Ma;Zhe Zhao;Xinyang Yi;Jilin Chen

  • The Case for Learned Index Structures

    Tim Kraska;Alex Beutel;Ed H. Chi;Jeffrey Dean

  • A taxonomy of visualization techniques using the data state reference model

    E.H. Chi

  • He says, she says: conflict and coordination in Wikipedia

    Aniket Kittur;Bongwon Suh;Bryan A. Pendleton;Ed H. Chi

  • Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

    Unknown

  • Tweets from Justin Bieber's heart: the dynamics of the location field in user profiles

    Brent Hecht;Lichan Hong;Bongwon Suh;Ed H. Chi

  • Using information scent to model user information needs and actions and the Web

    Ed H. Chi;Peter Pirolli;Kim Chen;James Pitkow

  • Short and tweet: experiments on recommending content from information streams

    Jilin Chen;Rowan Nairn;Les Nelson;Michael Bernstein

  • System and method for clustering data objects in a collection

    Hinrich Schuetze;Peter L. Pirolli;James E. Pitkow;Ed H. Chi

  • DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems

    Ruoxi Wang;Rakesh Shivanna;Derek Z. Cheng;Sagar Jain

  • System and method for providing recommendations based on multi-modal user clusters

    Hinrich Schuetze;James E. Pitkow;Peter L. Pirolli;Ed H. Chi

  • Data Decisions and Theoretical Implications when Adversarially Learning Fair Representations

    Alex Beutel;Ed H. Chi;Jilin Chen;Zhe Zhao

  • Top-K Off-Policy Correction for a REINFORCE Recommender System

    Minmin Chen;Alex Beutel;Paul Covington;Sagar Jain

  • ScentTrails: Integrating browsing and searching on the Web

    Christopher Olston;Ed H. Chi

  • An operator interaction framework for visualization systems

    Ed Huai-Hsin Chi;J.T. Riedl

  • Latent Cross: Making Use of Context in Recurrent Recommender Systems

    Alex Beutel;Paul Covington;Sagar Jain;Can Xu

  • Fairness in Recommendation Ranking through Pairwise Comparisons

    Alex Beutel;Jilin Chen;Tulsee Doshi;Hai Qian

  • The scent of a site: a system for analyzing and predicting information scent, usage, and usability of a Web site

    Ed H. Chi;Peter Pirolli;James Pitkow

  • System and method for quantitatively representing data objects in vector space

    Hinrich Schuetze;Francine R. Chen;Peter L. Pirolli;James E. Pitkow

  • Recommending what video to watch next: a multitask ranking system

    Zhe Zhao;Lichan Hong;Li Wei;Jilin Chen

  • Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

    Joseph A. Konstan;Ed H. Chi;Kristina Höök

Frequent Co-Authors

Lichan Hong
Lichan Hong Google (United States)
Peter Pirolli
Peter Pirolli Florida Institute for Human and Machine Cognition
James E. Pitkow
James E. Pitkow Palo Alto Research Center
Stuart K. Card
Stuart K. Card Stanford University
John Riedl
John Riedl University of Minnesota
Aniket Kittur
Aniket Kittur Carnegie Mellon University
Alex Beutel
Alex Beutel OpenAI
Michael S. Bernstein
Michael S. Bernstein Stanford University
Victoria Bellotti
Victoria Bellotti Palo Alto Research Center
Jock D. Mackinlay
Jock D. Mackinlay Tableau Software (United States)

External Links

Wikipedia of Ed H. Chi Personal website of Ed H. Chi Google Scholar page

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Best Scientists Citing Ed H. Chi

Jonathan J. Hull

Jonathan J. Hull

Independent Scientist / Consultant, US

Publications: 40

Aniket Kittur

Aniket Kittur

Carnegie Mellon University

Publications: 38

Michael S. Bernstein

Michael S. Bernstein

Stanford University

Publications: 34

Berna Erol

Berna Erol

Ricoh (Japan)

Publications: 34

Meredith Ringel Morris

Meredith Ringel Morris

Google (United States)

Publications: 32

Peter Pirolli

Peter Pirolli

Florida Institute for Human and Machine Cognition

Publications: 31

Robert R. Friedlander

Robert R. Friedlander

IBM (United States)

Publications: 27

Robert E. Kraut

Robert E. Kraut

Carnegie Mellon University

Publications: 26

Margaret Burnett

Margaret Burnett

Oregon State University

Publications: 25

John Riedl

John Riedl

University of Minnesota

Publications: 23

Brent Hecht

Brent Hecht

Northwestern University

Publications: 22

Geert-Jan Houben

Geert-Jan Houben

Delft University of Technology

Publications: 21

James R. Kraemer

James R. Kraemer

IBM (United States)

Publications: 21

Thomas R. Gruber

Thomas R. Gruber

Austrian Institute of Technology

Publications: 21

Chirag Shah

Chirag Shah

University of Washington

Publications: 21

Hugh Svendsen

Hugh Svendsen

Ikorongo Technology

Publications: 20

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2027 Best ADN Nursing Programs in Utah: Online & Campus
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2027 Best Online MBA Programs
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2027 How to Become a Special Education Teacher in San Francisco, CA: Education Requirements & Certification