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Danai Koutra

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 37 10541 10244 4419 4236 199 8210

Danai Koutra publications per year

The chart shows the history of publications by Danai Koutra between 2011 and 2025, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Danai Koutra published across 15 years, from 2011 to 2025, averaging 14.9 papers a year. Output peaked at 33 publications in 2021. 32 of the 223 publications appeared in the last two years.

No. of publications
10 20 30
Bar chart. Horizontal axis: year, 2011 to 2025. Vertical axis: number of publications, 0 to 33. Peak 33 publications in 2021. 2011: 2 publications 2012: 5 publications 2013: 9 publications 2014: 12 publications 2015: 10 publications 2016: 8 publications 2017: 13 publications 2018: 25 publications 2019: 17 publications 2020: 28 publications 2021: 33 publications 2022: 8 publications 2023: 21 publications 2024: 15 publications 2025: 17 publications
2011 2025

223 publications in total across all disciplines

View publications per year as a table
Danai Koutra: publications per year, 2011 to 2025
Year Publications
2011 2
2012 5
2013 9
2014 12
2015 10
2016 8
2017 13
2018 25
2019 17
2020 28
2021 33
2022 8
2023 21
2024 15
2025 17
Total 223
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Danai Koutra 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 Danai Koutra 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, 192–201 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: 199 publications — 46th percentile

46% 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
192–201 519 199
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
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

Danai Koutra 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 Danai Koutra 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, 36–37 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: 37 D-Index — 27th percentile

27% 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 37
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
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

Overview

Danai Koutra is affiliated with the University of Michigan-Ann Arbor in the United States. Their research primarily focuses on the field of Computer Science, with a specialization in Artificial Intelligence and related subfields. The breadth of their work extends into Statistical and Nonlinear Physics, Computer Vision and Pattern Recognition, Management Science and Operations Research, and Information Systems.

Their main topics of study include Advanced Graph Neural Networks, Complex Network Analysis Techniques, Topic Modeling, Data Quality and Management, Natural Language Processing Techniques, Explainable Artificial Intelligence (XAI), and Recommender Systems and Techniques.

Koutra has a substantial publication record with frequent venues including:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • ACM Transactions on Knowledge Discovery from Data
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing

Among recent papers authored or co-authored by Koutra are:

  • Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs, 2020, arXiv (Cornell University)
  • Graph Neural Networks with Heterophily, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Two Sides of the Same Coin: Heterophily and Oversmoothing in Graph Convolutional Neural Networks, 2022, 2022 IEEE International Conference on Data Mining (ICDM)
  • Democratizing EHR analyses with FIDDLE: a flexible data-driven preprocessing pipeline for structured clinical data, 2020, Journal of the American Medical Informatics Association

Danai Koutra frequently collaborates with various researchers, including Mark Heimann, Puja Trivedi, Di Jin, Tara Safavi, and Jiong Zhu.

Their contributions to academic literature also include several book publications with Springer Science+Business Media, notably titles related to Machine Learning and Knowledge Discovery in Databases published in 2023.

Best Publications

  • Graph based anomaly detection and description: a survey

    Leman Akoglu;Hanghang Tong;Danai Koutra

  • RolX: structural role extraction & mining in large graphs

    Keith Henderson;Brian Gallagher;Tina Eliassi-Rad;Hanghang Tong

  • Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs

    Jiong Zhu;Yujun Yan;Lingxiao Zhao;Mark Heimann

  • Anomaly detection in dynamic networks: a survey

    Stephen Ranshous;Stephen Ranshous;Shitian Shen;Shitian Shen;Danai Koutra;Steve Harenberg;Steve Harenberg

  • Graph Summarization Methods and Applications: A Survey

    Yike Liu;Tara Safavi;Abhilash Dighe;Danai Koutra

  • DELTACON: A Principled Massive-Graph Similarity Function

    Unknown

  • DELTACON: A principled massive-graph similarity function

    Danai Koutra;Joshua T. Vogelstein;Christos Faloutsos

  • Graph Neural Networks with Heterophily.

    Jiong Zhu;Ryan A. Rossi;Anup B. Rao;Tung Mai

  • Graph Neural Networks with Heterophily

    Jiong Zhu;Ryan A. Rossi;Anup Rao;Tung Mai

  • Detecting insider threats in a real corporate database of computer usage activity

    Ted E. Senator;Henry G. Goldberg;Alex Memory;William T. Young

  • Beyond Homophily in Graph Neural Networks: Current Limitations and Effective Designs

    Jiong Zhu;Yujun Yan;Lingxiao Zhao;Mark Heimann

  • BIG-ALIGN: Fast Bipartite Graph Alignment

    Danai Koutra;Hanghang Tong;David Lubensky

  • TimeCrunch: Interpretable Dynamic Graph Summarization

    Neil Shah;Danai Koutra;Tianmin Zou;Brian Gallagher

  • DeltaCon: Principled Massive-Graph Similarity Function with Attribution

    Danai Koutra;Neil Shah;Joshua T. Vogelstein;Brian Gallagher

  • REGAL: Representation Learning-based Graph Alignment

    Mark Heimann;Haoming Shen;Tara Safavi;Danai Koutra

  • VoG: Summarizing and understanding large graphs

    Danai Koutra;U Kang;Jilles Vreeken;Christos Faloutsos

  • Unifying guilt-by-association approaches: theorems and fast algorithms

    Danai Koutra;Tai-You Ke;U. Kang;Duen Horng Polo Chau

  • DELTACON: A Principled Massive-Graph Similarity Function

    Danai Koutra;Joshua T. Vogelstein;Christos Faloutsos

  • Com2: Fast Automatic Discovery of Temporal ( Comet ) Communities

    Miguel Araujo;Miguel Araujo;Spiros Papadimitriou;Stephan Günnemann;Christos Faloutsos

  • NetSimile: A Scalable Approach to Size-Independent Network Similarity

    Michele Berlingerio;Danai Koutra;Tina Eliassi-Rad;Christos Faloutsos

  • Glance: rapidly coding behavioral video with the crowd

    Walter S. Lasecki;Mitchell Gordon;Danai Koutra;Malte F. Jung

  • Network similarity via multiple social theories

    Michele Berlingerio;Danai Koutra;Tina Eliassi-Rad;Christos Faloutsos

  • A Graph Summarization: A Survey.

    Yike Liu;Abhilash Dighe;Tara Safavi;Danai Koutra

  • Graph Summarization: A Survey

    Yike Liu;Abhilash Dighe;Tara Safavi;Danai Koutra

Frequent Co-Authors

Christos Faloutsos
Christos Faloutsos Carnegie Mellon University
Evangelos E. Papalexakis
Evangelos E. Papalexakis University of California, Riverside
U Kang
U Kang Seoul National University
Leman Akoglu
Leman Akoglu Carnegie Mellon University
Jilles Vreeken
Jilles Vreeken Max Planck Society
Chandra Sripada
Chandra Sripada University of Michigan–Ann Arbor
Stephan Günnemann
Stephan Günnemann Technical University of Munich
Nesreen K. Ahmed
Nesreen K. Ahmed Intel (United States)
Paul N. Bennett
Paul N. Bennett Microsoft (United States)
Joshua T. Vogelstein
Joshua T. Vogelstein Johns Hopkins University

External Links

Personal website of Danai Koutra

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Best Scientists Citing Danai Koutra

Christos Faloutsos

Christos Faloutsos

Carnegie Mellon University

Publications: 51

Evangelos E. Papalexakis

Evangelos E. Papalexakis

University of California, Riverside

Publications: 29

Nesreen K. Ahmed

Nesreen K. Ahmed

Intel (United States)

Publications: 26

Philip S. Yu

Philip S. Yu

University of Illinois at Chicago

Publications: 24

Hanghang Tong

Hanghang Tong

University of Illinois at Urbana-Champaign

Publications: 21

U Kang

U Kang

Seoul National University

Publications: 21

Tina Eliassi-Rad

Tina Eliassi-Rad

Northeastern University

Publications: 20

Leman Akoglu

Leman Akoglu

Carnegie Mellon University

Publications: 19

Jure Leskovec

Jure Leskovec

Stanford University

Publications: 16

Xueqi Cheng

Xueqi Cheng

Chinese Academy of Sciences

Publications: 16

Nitesh V. Chawla

Nitesh V. Chawla

University of Notre Dame

Publications: 14

Jeffrey P. Bigham

Jeffrey P. Bigham

Carnegie Mellon University

Publications: 14

Huawei Shen

Huawei Shen

Chinese Academy of Sciences

Publications: 14

Sheng Hua Liu

Sheng Hua Liu

Central China Normal University

Publications: 13

Michalis Faloutsos

Michalis Faloutsos

University of California, Riverside

Publications: 13

Carey E. Priebe

Carey E. Priebe

Johns Hopkins University

Publications: 13

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