World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
7166
World Ranking
7280
National Ranking
434

Vladimir Stankovic 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 Vladimir Stankovic 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: 302 publications — 74th percentile

74% of scientists in this discipline score the same or lower.

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

Vladimir Stankovic 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 Vladimir Stankovic 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: 45 D-Index — 51st percentile

51% of scientists in this discipline score the same or lower.

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

Overview

Vladimir Stankovic is affiliated with the University of Strathclyde in the United Kingdom. Their research spans multiple disciplines within engineering and computer science, with a strong emphasis on artificial intelligence and electrical and electronic engineering.

Their main fields of study include:

  • Engineering
  • Computer Science

Within these fields, Stankovic has contributed to several subfields such as:

  • Artificial Intelligence
  • Electrical and Electronic Engineering
  • Computer Networks and Communications
  • Geophysics
  • Control and Systems Engineering

The primary topics covered by their work consist of:

  • Smart Grid Energy Management
  • Seismology and Earthquake Studies
  • Landslides and related hazards
  • Energy Load and Power Forecasting
  • Smart Grid Security and Resilience
  • Building Energy and Comfort Optimization
  • Seismic Imaging and Inversion Techniques

Stankovic has published extensively in renowned venues, including:

  • Sensors
  • SSRN Electronic Journal
  • Applied Energy
  • arXiv (Cornell University)
  • IEEE Transactions on Geoscience and Remote Sensing

Their recent publications include:

  • A Survey on Deep Reinforcement Learning Algorithms for Robotic Manipulation, 2023, Sensors
  • Non-intrusive load disaggregation solutions for very low-rate smart meter data, 2020, Applied Energy
  • Transfer learning for multi-objective non-intrusive load monitoring in smart building, 2022, Applied Energy
  • An active learning framework for the low-frequency Non-Intrusive Load Monitoring problem, 2023, Applied Energy
  • Averaging Is Probably Not the Optimum Way of Aggregating Parameters in Federated Learning, 2020, Entropy

Frequent collaborators in their research include:

  • Lina Stanković
  • Stella Pytharouli
  • Samuel Cheng
  • Apostolos Vavouris
  • Djordje Batic

Best Publications

  • An electrical load measurements dataset of United Kingdom households from a two-year longitudinal study.

    David Murray;Lina Stankovic;Vladimir Stankovic

  • Non-Intrusive Load Disaggregation Using Graph Signal Processing

    Kanghang He;Lina Stankovic;Jing Liao;Vladimir Stankovic

  • On a Training-Less Solution for Non-Intrusive Appliance Load Monitoring Using Graph Signal Processing

    Bochao Zhao;Lina Stankovic;Vladimir Stankovic

  • A Survey on Deep Reinforcement Learning Algorithms for Robotic Manipulation

    Unknown

  • Scalable Video Multicast Using Expanding Window Fountain Codes

    D. Vukobratovic;V. Stankovic;D. Sejdinovic;L. Stankovic

  • On code design for the Slepian-Wolf problem and lossless multiterminal networks

    V. Stankovic;A.D. Liveris;Zixiang Xiong;C.N. Georghiades

  • Compressive Sampling of Binary Images

    Vladimir Stankovic;Lina Stankovic;Samuel Cheng

  • Distributed joint source-channel coding of video using raptor codes

    Qian Xu;V. Stankovic;Zixiang Xiong

  • Non-intrusive appliance load monitoring using low-resolution smart meter data

    Jing Liao;Georgia Elafoudi;Lina Stankovic;Vladimir Stankovic

  • Transferability of Neural Network Approaches for Low-rate Energy Disaggregation

    David Murray;Lina Stankovic;Vladimir Stankovic;Srdjan Lulic

  • Cooperative diversity for wireless ad hoc networks

    V. Stankovic;A. Host-Madsen;Zixiang Xiong

  • Design of Slepian-Wolf codes by channel code partitioning

    V. Stankovic;A.D. Liveris;Zixiang Xiong;C.N. Georghiades

  • Can non-intrusive load monitoring be used for identifying an appliance's anomalous behaviour?

    Haroon Rashid;Pushpendra Singh;Vladimir Stankovic;Lina Stankovic

  • Improving Event-Based Non-Intrusive Load Monitoring Using Graph Signal Processing

    Bochao Zhao;Kanghang He;Lina Stankovic;Vladimir Stankovic

  • Optimized error protection of scalable image bit streams [advances in joint source-channel coding for images]

    R. Hamzaoui;V. Stankovic;Zixiang Xiong

  • Measuring the energy intensity of domestic activities from smart meter data

    L. Stankovic;V. Stankovic;J. Liao;C. Wilson

  • A data management platform for personalised real-time energy feedback

    David Murray;Jing Liao;Lina Stankovic;Vladimir Stankovic

  • Real-time error protection of embedded codes for packet erasure and fading channels

    V.M. Stankovic;R. Hamzaoui;Zixiang Xiong

  • Wyner-Ziv coding for the half-duplex relay channel

    Zhixin Liu;V. Stankovic;Zixiang Xiong

  • On Multiterminal Source Code Design

    Yang Yang;V. Stankovic;Zixiang Xiong;Wei Zhao

  • Fast algorithm for rate-based optimal error protection of embedded codes

    V. Stankovic;R. Hamzaoui;D. Saupe

Frequent Co-Authors

Zixiang Xiong
Zixiang Xiong Texas A&M University
Gene Cheung
Gene Cheung York University
Wei Zhao
Wei Zhao Shenzhen Institutes of Advanced Technology
Cedomir Stefanovic
Cedomir Stefanovic Aalborg University
Jacob Chakareski
Jacob Chakareski New Jersey Institute of Technology
Charles B. Wilson
Charles B. Wilson University of California, San Francisco
Dietmar Saupe
Dietmar Saupe University of Konstanz
Costas N. Georghiades
Costas N. Georghiades Texas A&M University
Pavel Cheben
Pavel Cheben National Research Council Canada
Ivan Andonovic
Ivan Andonovic University of Strathclyde

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring online degrees in Computer Science has never been more accessible. For students concerned about cost, there are cheapest online degrees available, providing quality education at an affordable price point.

Academic requirements vary, and if your GPA isn’t stellar, don’t worry — there are many online schools that accept low gpa. This means more students can get started on their computer science journey.

In addition to traditional pathways, some may consider cross-disciplinary careers. For example, graduates often wonder: what can i do with an environmental science degree? Combining skills from both fields can open doors in data analysis, sustainability tech, and more.

For those eager to enter the workforce quickly, consider the accelerated computer science degree options online. These programs help students finish faster and start their careers sooner.

Best Scientists Citing Vladimir Stankovic

Trending Scientists

Recently Published Articles