World's Best Scientists 2026 revealed!
Jason J. Jung

Jason J. Jung

D-Index & Metrics

Computer Science

D-Index
41
Citations
6947
World Ranking
8852
National Ranking
92

Jason J. Jung 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 Jason J. Jung 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: 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 publications 991+

This scientist: 378 publications — 85th percentile

85% of scientists in this discipline score the same or lower.

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

Jason J. Jung 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 Jason J. Jung sits on this spectrum.

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 D-Index 131+

This scientist: 41 D-Index — 40th percentile

40% of scientists in this discipline score the same or lower.

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

Overview

Jason J. Jung is affiliated with Chung-Ang University in South Korea, where their research primarily focuses on computer science with an emphasis on artificial intelligence and related subfields.

Their work spans multiple specialized areas within computer science, including:

  • Artificial Intelligence
  • Information Systems
  • Computer Vision and Pattern Recognition
  • Statistical and Nonlinear Physics
  • Computer Networks and Communications

The main research topics covered by Jason J. Jung include:

  • Recommender Systems and Techniques
  • Complex Network Analysis Techniques
  • Topic Modeling
  • Anomaly Detection Techniques and Applications
  • Image Retrieval and Classification Techniques
  • Traffic Prediction and Management Techniques
  • Transportation Planning and Optimization

Jason J. Jung has published extensively in various venues, with frequent contributions to:

  • TUGraz OPEN Library (Graz University of Technology)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Applied Sciences
  • Expert Systems
  • PLoS ONE

Significant recent papers include:

  • "Deep learning for anomaly detection in multivariate time series: Approaches, applications, and challenges," 2022, Information Fusion
  • "Knowledge graph fusion for smart systems: A Survey," 2020, Information Fusion
  • "Cognitive Similarity-Based Collaborative Filtering Recommendation System," 2020, Applied Sciences
  • "Evolving Generative Adversarial Networks to improve image steganography," 2023, Expert Systems with Applications
  • "Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges," 2020, Sustainability

Their frequent collaborators include:

  • Gen Li
  • Luong Vuong Nguyen
  • Tri-Hai Nguyen
  • Minsung Hong
  • David Camacho

Best Publications

  • Social big data

    Gema Bello-Orgaz;Jason J. Jung;David Camacho

  • Examination of how social aspects moderate the relationship between task characteristics and usage of social communication technologies (SCTs) in organizations

    Chulmo Koo;Yulia Wati;Jason J. Jung

  • Towards Semantic Social Networks

    Jason J. Jung;Jérôme Euzenat

  • Service chain-based business alliance formation in service-oriented architecture

    Jason J. Jung

  • Reusing ontology mappings for query routing in semantic peer-to-peer environment

    Jason J. Jung

  • Semantic business process integration based on ontology alignment

    Jason J. Jung

  • Knowledge graph fusion for smart systems: A Survey

    Hoang Long Nguyen;Dang Thinh Vu;Jason J. Jung

  • Deep learning for EEG data analytics: A survey

    Gen Li;Chang Ha Lee;Jason J. Jung;Young Chul Youn

  • Attribute selection-based recommendation framework for short-head user group: An empirical study by MovieLens and IMDB

    Jason J. Jung

  • Online named entity recognition method for microtexts in social networking services: A case study of twitter

    Jason J. Jung

  • Exploiting matrix factorization to asymmetric user similarities in recommendation systems

    Parivash Pirasteh;Dosam Hwang;Jason J. Jung

  • Real world representation of a road network for route planning in GIS

    Abolghasem Sadeghi-Niaraki;Masood Varshosaz;Kyehyun Kim;Jason J. Jung

  • Ontology-based context synchronization for ad hoc social collaborations

    Jason J. Jung

  • Contextualized mobile recommendation service based on interactive social network discovered from mobile users

    Jason J. Jung

  • Ontological framework based on contextual mediation for collaborative information retrieval

    Jason J. Jung

  • Query Transformation Based on Semantic Centrality in Semantic Social Network1.

    Jason J. Jung

  • Social recommendation service for cultural heritage

    Minsung Hong;Jason J. Jung;Francesco Piccialli;Angelo Chianese

  • Cognitive Similarity-Based Collaborative Filtering Recommendation System

    Luong Vuong Nguyen;Min-Sung Hong;Jason J. Jung;Bong-Soo Sohn

  • Cooperative game-theoretic approach to traffic flow optimization for multiple intersections

    Khac-Hoai Nam Bui;Jason J. Jung

  • Item-Based Collaborative Filtering with Attribute Correlation: A Case Study on Movie Recommendation

    Parivash Pirasteh;Jason J. Jung;Dosam Hwang

  • ACO-Based Dynamic Decision Making for Connected Vehicles in IoT System

    Khac-Hoai Nam Bui;Jason J. Jung

  • Complexity Analysis of Ontology Integration Methodologies: a Comparative Study

    Trong Hai Duong;Geun Sik Jo;Jason J. Jung;Ngoc Thanh Nguyen

Frequent Co-Authors

David Camacho
David Camacho Technical University of Madrid
Francesco Piccialli
Francesco Piccialli University of Naples Federico II
Jérôme Euzenat
Jérôme Euzenat Grenoble Alpes University
Simon Fong
Simon Fong University of Macau
Rafidah Md Noor
Rafidah Md Noor University of Malaya
Chulmo Koo
Chulmo Koo Kyung Hee University
Ali Selamat
Ali Selamat University of Technology Malaysia
Bay Vo
Bay Vo Ho Chi Minh City University of Technology
Tzung-Pei Hong
Tzung-Pei Hong National University of Kaohsiung
Feng Xia
Feng Xia RMIT University

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