World's Best Scientists 2026 revealed!
Evgeny Kharlamov

Evgeny Kharlamov

D-Index & Metrics

Computer Science

D-Index
34
Citations
4262
World Ranking
12263
National Ranking
42

Evgeny Kharlamov 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 Evgeny Kharlamov 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: 230 publications — 57th percentile

57% of scientists in this discipline score the same or lower.

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

Evgeny Kharlamov 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 Evgeny Kharlamov 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: 34 D-Index — 16th percentile

16% of scientists in this discipline score the same or lower.

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

Overview

Evgeny Kharlamov is affiliated with the University of Oslo in Norway. Their research primarily spans the field of Computer Science, with significant contributions to several subfields including Artificial Intelligence, Management Science and Operations Research, Information Systems, Computer Networks and Communications, and Industrial and Manufacturing Engineering.

Kharlamov's work covers a range of topics, with a strong focus on Advanced Graph Neural Networks and Semantic Web and Ontologies. Other notable research topics include Data Quality and Management, Topic Modeling, Data Management and Algorithms, Bayesian Modeling and Causal Inference, and Rough Sets and Fuzzy Logic.

Their publication record includes papers in a variety of reputable venues. Frequent places of publication are arXiv (Cornell University), IEEE Transactions on Knowledge and Data Engineering, Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Zenodo (CERN European Organization for Nuclear Research), and the Proceedings of the ACM Web Conference 2022.

Representative recent papers include:

  • Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding, 2022, Journal of Intelligent Manufacturing
  • SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs, 2022, Proceedings of the ACM Web Conference 2022
  • GCCAD: Graph Contrastive Learning for Anomaly Detection, 2022, IEEE Transactions on Knowledge and Data Engineering
  • SemML: Facilitating development of ML models for condition monitoring with semantics, 2021, Journal of Web Semantics
  • GRAND+: Scalable Graph Random Neural Networks, 2022, Proceedings of the ACM Web Conference 2022

Collaboratively, Kharlamov has frequently worked with several coauthors. Some of the often-collaborating researchers include Baifan Zhou, Ahmet Soylu, Zhuoxun Zheng, Dongzhuoran Zhou, and Gong Cheng.

Best Publications

  • Graph Random Neural Networks for Semi-Supervised Learning on Graphs

    Wenzheng Feng;Jie Zhang;Yuxiao Dong;Yu Han

  • Faceted search over RDF-based knowledge graphs

    Marcelo Arenas;Bernardo Cuenca Grau;Evgeny Kharlamov;Šarunas Marciuška

  • Evolution of DL-lite knowledge bases

    Diego Calvanese;Evgeny Kharlamov;Werner Nutt;Dmitriy Zheleznyakov

  • Ontology Based Data Access in Statoil

    Evgeny Kharlamov;Dag Hovland;Martin G Skjæveland;Dimitris Bilidas

  • BootOX: Practical Mapping of RDBs to OWL 2

    Ernesto Jiménez-Ruiz;Evgeny Kharlamov;Dmitriy Zheleznyakov;Ian Horrocks

  • How Semantic Technologies Can Enhance Data Access at Siemens Energy

    Evgeny Kharlamov;Nina Solomakhina;Özgür Lütfü Özçep;Dmitriy Zheleznyakov

  • Semantic access to streaming and static data at Siemens

    Evgeny Kharlamov;Theofilos Mailis;Gulnar Mehdi;Christian Neuenstadt

  • Rule Learning from Knowledge Graphs Guided by Embedding Models

    Vinh Thinh Ho;Daria Stepanova;Mohamed Hassan Gad-Elrab;Evgeny Kharlamov

  • OptiqueVQS: a Visual Query System over Ontologies for Industry

    Ahmet Soylu;Evgeny Kharlamov;Dmitriy Zheleznyakov;Ernesto Jimenez-Ruiz

  • Ontology Based Access to Exploration Data at Statoil

    Evgeny Kharlamov;Dag Hovland;Ernesto Jiménez-Ruiz;Davide Lanti

  • Optique: Towards OBDA Systems for Industry

    Evgeny Kharlamov;Ernesto Jiménez-Ruiz;Dmitriy Zheleznyakov;Dimitris Bilidas

  • Capturing Industrial Information Models with Ontologies and Constraints

    Evgeny Kharlamov;Bernardo Cuenca Grau;Ernesto Jiménez-Ruiz;Steffen Lamparter

  • Ontology-Based Integration of Streaming and Static Relational Data with Optique

    Evgeny Kharlamov;Sebastian Brandt;Ernesto Jimenez-Ruiz;Yannis Kotidis

  • OptiqueVQS: towards an ontology-based visual query system for big data

    Ahmet Soylu;Martin Giese;Ernesto Jimenez-Ruiz;Evgeny Kharlamov

  • SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs

    Unknown

  • Using Semantic Technology to Tame the Data Variety Challenge

    Ian Horrocks;Martin Giese;Evgeny Kharlamov;Arild Waaler

  • GCCAD: Graph Contrastive Learning for Anomaly Detection

    Unknown

  • Faceted Search over Ontology-Enhanced RDF Data

    Marcelo Arenas;Bernardo Cuenca Grau;Evgeny Kharlamov;Sarunas Marciuska

  • SemFacet: semantic faceted search over yago

    Marcelo Arenas;Bernardo Cuenca Grau;Evgeny Kharlamov;Sarunas Marciuska

  • Aggregate queries for discrete and continuous probabilistic XML

    Serge Abiteboul;T.-H. Hubert Chan;Evgeny Kharlamov;Werner Nutt

  • Capturing model-based ontology evolution at the instance level: The case of DL-Lite

    Evgeny Kharlamov;Dmitriy Zheleznyakov;Diego Calvanese

  • TDGIA: Effective Injection Attacks on Graph Neural Networks

    Xu Zou;Qinkai Zheng;Yuxiao Dong;Xinyu Guan

Frequent Co-Authors

Ian Horrocks
Ian Horrocks University of Oxford
Ernesto Jiménez-Ruiz
Ernesto Jiménez-Ruiz City, University of London
Diego Calvanese
Diego Calvanese Free University of Bozen-Bolzano
Bernardo Cuenca Grau
Bernardo Cuenca Grau University of Oxford
Yannis E. Ioannidis
Yannis E. Ioannidis National and Kapodistrian University of Athens
Yannis Kotidis
Yannis Kotidis Athens University of Economics and Business
Werner Nutt
Werner Nutt Free University of Bozen-Bolzano
Ralf Möller
Ralf Möller University of Lübeck
Jie Tang
Jie Tang Tsinghua University
Peter Haase
Peter Haase Metaphacts

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