World's Best Scientists 2026 revealed!
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Longbing Cao
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Computer Science
Australia
2025

D-Index & Metrics

Discipline name D-Index World Ranking Current World Ranking National Ranking Current National Ranking Publications Citations
Computer Science 64 2550 2471 77 76 505 21014

Longbing Cao publications per year

The chart shows the history of publications by Longbing Cao between 2002 and 2026, highlighting the no. of papers published in each year and offering an overview of the publication velocity of this scholar. Longbing Cao published across 25 years, from 2002 to 2026, averaging 23.7 papers a year. Output peaked at 51 publications in 2013. 10 of the 593 publications appeared in the last two years.

No. of publications
10 20 30 40 50
Bar chart. Horizontal axis: year, 2002 to 2026. Vertical axis: number of publications, 0 to 51. Peak 51 publications in 2013. 2002: 1 publication 2003: 7 publications 2004: 7 publications 2005: 9 publications 2006: 11 publications 2007: 18 publications 2008: 35 publications 2009: 29 publications 2010: 32 publications 2011: 17 publications 2012: 31 publications 2013: 51 publications 2014: 32 publications 2015: 38 publications 2016: 17 publications 2017: 24 publications 2018: 39 publications 2019: 17 publications 2020: 23 publications 2021: 43 publications 2022: 30 publications 2023: 44 publications 2024: 28 publications 2025: 9 publications 2026: 1 publication
2002 2026

593 publications in total across all disciplines

View publications per year as a table
Longbing Cao: publications per year, 2002 to 2026
Year Publications
2002 1
2003 7
2004 7
2005 9
2006 11
2007 18
2008 35
2009 29
2010 32
2011 17
2012 31
2013 51
2014 32
2015 38
2016 17
2017 24
2018 39
2019 17
2020 23
2021 43
2022 30
2023 44
2024 28
2025 9
2026 1
Total 593
Download as CSV

Longbing Cao 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 Longbing Cao 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, 502–511 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: 505 publications — 93rd percentile

93% 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
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 54 505
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

Longbing Cao 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 Longbing Cao 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, 64–65 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: 64 D-Index — 82nd percentile

82% 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 64
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

Research.com Recognitions

  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2023 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award
  • 2020 - ACM Distinguished Member

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of investigation include Data science, Artificial intelligence, Data mining, Knowledge extraction and Machine learning. His Data science research integrates issues from Domain, Field, Information technology and Knowledge management. His study in Artificial intelligence is interdisciplinary in nature, drawing from both Contrast and Pattern recognition.

His Data mining research is multidisciplinary, relying on both Information extraction, Algorithm design and Pruning. His research in Knowledge extraction intersects with topics in Association rule learning, Autonomous agent, Decision support system and Domain knowledge. His work carried out in the field of Machine learning brings together such families of science as Fuzzy set operations and Fuzzy classification.

His most cited work include:

  • Training deep neural networks on imbalanced data sets (165 citations)
  • Personalized recommendation via cross-domain triadic factorization (162 citations)
  • USpan: an efficient algorithm for mining high utility sequential patterns (156 citations)

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

His primary areas of study are Data mining, Artificial intelligence, Data science, Pattern recognition and Machine learning. His studies in Data mining integrate themes in fields like Multi-agent system and Cluster analysis. His research on Artificial intelligence frequently connects to adjacent areas such as Categorical variable.

His Data science research includes themes of Domain, Actionable knowledge, Knowledge extraction and Knowledge management. Longbing Cao studies Pattern recognition, focusing on Feature selection in particular. Longbing Cao is studying Recommender system, which is a component of Machine learning.

He most often published in these fields:

  • Data mining (30.00%)
  • Artificial intelligence (29.30%)
  • Data science (23.72%)

What were the highlights of his more recent work (between 2017-2021)?

  • Data science (23.72%)
  • Artificial intelligence (29.30%)
  • Recommender system (8.14%)

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

Data science, Artificial intelligence, Recommender system, Anomaly detection and Theoretical computer science are his primary areas of study. The concepts of his Data science study are interwoven with issues in Order, Key and Big data. His Artificial intelligence research includes themes of Machine learning, Categorical variable and Pattern recognition.

His Recommender system research incorporates elements of Intelligent decision support system, Preference and Categorization. Longbing Cao undertakes interdisciplinary study in the fields of Focus and Data mining through his works. His Data mining study integrates concerns from other disciplines, such as Principle of maximum entropy and Hash function.

Between 2017 and 2021, his most popular works were:

  • GeoMF++: Scalable Location Recommendation via Joint Geographical Modeling and Matrix Factorization (50 citations)
  • Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection (49 citations)
  • Attention-based transactional context embedding for next-item recommendation (46 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Longbing Cao focuses on Recommender system, Artificial intelligence, Data science, Data mining and Key. To a larger extent, he studies Machine learning with the aim of understanding Recommender system. His work in Artificial intelligence is not limited to one particular discipline; it also encompasses Pattern recognition.

His Pattern recognition research integrates issues from Leverage and Cluster analysis. His studies deal with areas such as Cold start recommendation, Relation, Categorization and Interpretability as well as Data science. His work carried out in the field of Data mining brings together such families of science as Bitmap, Data structure and Computer data storage.

Best Publications

  • Deep Learning for Anomaly Detection: A Review

    Guansong Pang;Chunhua Shen;Longbing Cao;Anton Van Den Hengel

  • Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

    Longbing Cao;Chengqi Zhang;Thorsten Joachims;Geoff Webb

  • Sequential Recommender Systems: Challenges, Progress and Prospects

    Shoujin Wang;Liang Hu;Liang Hu;Yan Wang;Longbing Cao

  • A Survey on Session-based Recommender Systems

    Shoujin Wang;Longbing Cao;Yan Wang;Quan Z. Sheng

  • Training deep neural networks on imbalanced data sets

    Shoujin Wang;Wei Liu;Jia Wu;Longbing Cao

  • Effective detection of sophisticated online banking fraud on extremely imbalanced data

    Wei Wei;Jinjiu Li;Longbing Cao;Yuming Ou

  • Personalized recommendation via cross-domain triadic factorization

    Liang Hu;Jian Cao;Guandong Xu;Longbing Cao

  • USpan: an efficient algorithm for mining high utility sequential patterns

    Junfu Yin;Zhigang Zheng;Longbing Cao

  • Data Science: A Comprehensive Overview

    Longbing Cao

  • Decentralized AI: Edge Intelligence and Smart Blockchain, Metaverse, Web3, and DeSci

    Unknown

  • In-depth behavior understanding and use: The behavior informatics approach

    Longbing Cao

  • Data Science: A Comprehensive Overview

    Longbing Cao

  • Attention-based transactional context embedding for next-item recommendation

    Shoujin Wang;Liang Hu;Longbing Cao;Xiaoshui Huang

  • Coupled Behavior Analysis with Applications

    Longbing Cao;Yuming Ou;Philip S. Yu

  • Learning Representations of Ultrahigh-dimensional Data for Random Distance-based Outlier Detection

    Guansong Pang;Longbing Cao;Ling Chen;Huan Liu

  • Domain-Driven Data Mining: Challenges and Prospects

    Longbing Cao

  • SVDD-based outlier detection on uncertain data

    Bo Liu;Yanshan Xiao;Longbing Cao;Zhifeng Hao

  • Agent Mining: The Synergy of Agents and Data Mining

    Longbing Cao;V. Gorodetsky;P.A. Mitkas

  • Graph learning based recommender systems: a review

    Shoujin Wang;Liang Hu;Yan Wang;Xiangnan He

  • Coupling Learning of Complex Interactions

    Longbing Cao

  • Data science: challenges and directions

    Longbing Cao

Frequent Co-Authors

Chengqi Zhang
Chengqi Zhang Hong Kong Polytechnic University
Philip S. Yu
Philip S. Yu University of Illinois at Chicago
Guandong Xu
Guandong Xu University of Technology Sydney
Hiroshi Motoda
Hiroshi Motoda Osaka University
Wei Wei
Wei Wei University of Technology Sydney
Jian Pei
Jian Pei Duke University
Vincent S. Tseng
Vincent S. Tseng National Yang Ming Chiao Tung University
Yan Wang
Yan Wang Macquarie University
Yang Gao
Yang Gao Google (United Kingdom)
Mehmet A. Orgun
Mehmet A. Orgun Macquarie University

External Links

Wikipedia of Longbing Cao Personal website of Longbing Cao Google Scholar page

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Publications: 30

Wensheng Gan

Wensheng Gan

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Publications: 29

Shitong Wang

Shitong Wang

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Publications: 23

Hongzhi Yin

Hongzhi Yin

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Publications: 19

Alok Sharma

Alok Sharma

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Publications: 19

Vincent S. Tseng

Vincent S. Tseng

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Publications: 18

Abdollah Dehzangi

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Rutgers, The State University of New Jersey

Publications: 17

Han-Chieh Chao

Han-Chieh Chao

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Publications: 16

Chengqi Zhang

Chengqi Zhang

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Publications: 15

Jie Lu

Jie Lu

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Publications: 14

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Publications: 14

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