World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
36
Citations
6090
World Ranking
11183
National Ranking
85

John B. Theocharis 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 John B. Theocharis 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: 115 publications — 13th percentile

13% of scientists in this discipline score the same or lower.

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

John B. Theocharis 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 John B. Theocharis 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: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

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

Overview

John B. Theocharis is affiliated with Aristotle University of Thessaloniki in Greece. Their research spans multiple fields, including Medicine, Environmental Science, and Computer Science, with a stronger focus on subfields such as Environmental Engineering and Artificial Intelligence.

Their academic work covers a variety of scientific topics. These include:

  • Soil Geostatistics and Mapping
  • Osteoarthritis Treatment and Mechanisms
  • Spectroscopy and Chemometric Analyses
  • Geochemistry and Geologic Mapping
  • Remote Sensing in Agriculture
  • Diabetic Foot Ulcer Assessment and Management
  • Mineral Processing and Grinding

Their recent publications include several papers mainly published between 2020 and 2021, reflecting interdisciplinary research combining environmental science and computer science approaches. Notable papers are:

  • Simultaneous prediction of soil properties from VNIR-SWIR spectra using a localized multi-channel 1-D convolutional neural network, 2020, Geoderma
  • An integrated methodology using open soil spectral libraries and Earth Observation data for soil organic carbon estimations in support of soil-related SDGs, 2020, Remote Sensing of Environment
  • Employing a Multi-Input Deep Convolutional Neural Network to Derive Soil Clay Content from a Synergy of Multi-Temporal Optical and Radar Imagery Data, 2020, Remote Sensing
  • Using autoencoders to compress soil VNIR-SWIR spectra for more robust prediction of soil properties, 2021, Geoderma
  • A three-level Multiple-Kernel Learning approach for soil spectral analysis, 2020, Neurocomputing

The frequent co-authors collaborating with John B. Theocharis include:

  • Nikolaos Tsakiridis
  • Andreas L. Symeonidis
  • Christos G. Chadoulos
  • George Zalidis
  • Serafeim Moustakidis

In terms of publishing venues, their work appears predominantly in journals and conferences focused on environmental science and machine learning. These venues include:

  • Geoderma
  • Machine Learning and Knowledge Extraction
  • Remote Sensing of Environment
  • Remote Sensing
  • Bioengineering

Best Publications

  • Long-term wind speed and power forecasting using local recurrent neural network models

    T.G. Barbounis;J.B. Theocharis;M.C. Alexiadis;P.S. Dokopoulos

  • A fuzzy model for wind speed prediction and power generation in wind parks using spatial correlation

    I.G. Damousis;M.C. Alexiadis;J.B. Theocharis;P.S. Dokopoulos

  • A recurrent fuzzy-neural model for dynamic system identification

    P.A. Mastorocostas;J.B. Theocharis

  • Short term load forecasting using fuzzy neural networks

    A.G. Bakirtzis;J.B. Theocharis;S.J. Kiartzis;K.J. Satsios

  • Locally recurrent neural networks for wind speed prediction using spatial correlation

    T. G. Barbounis;J. B. Theocharis

  • A locally recurrent fuzzy neural network with application to the wind speed prediction using spatial correlation

    T. G. Barbounis;J. B. Theocharis

  • A genetic algorithm solution approach to the hydrothermal coordination problem

    C.E. Zoumas;A.G. Bakirtzis;J.B. Theocharis;V. Petridis

  • A novel approach to short-term load forecasting using fuzzy neural networks

    S.E. Papadakis;J.B. Theocharis;S.J. Kiartzis;A.G. Bakirtzis

  • Microgenetic algorithms as generalized hill-climbing operators for GA optimization

    S.A. Kazarlis;S.E. Papadakis;J.B. Theocharis;V. Petridis

  • Locally recurrent neural networks for long-term wind speed and power prediction

    T. G. Barbounis;J. B. Theocharis

  • Fuzzy modeling for short term load forecasting using the orthogonal least squares method

    P.A. Mastorocostas;J.B. Theocharis;A.G. Bakirtzis

  • Simultaneous prediction of soil properties from VNIR-SWIR spectra using a localized multi-channel 1-D convolutional neural network

    Nikolaos L. Tsakiridis;Konstantinos D. Keramaris;John B. Theocharis;George C. Zalidis

  • SVM-Based Fuzzy Decision Trees for Classification of High Spatial Resolution Remote Sensing Images

    S. Moustakidis;G. Mallinis;N. Koutsias;J. B. Theocharis

  • A GA-based fuzzy modeling approach for generating TSK models

    S. E. Papadakis;J. B. Theocharis

  • A fuzzy expert system for peak load forecasting. Application to the Greek power system

    S.J. Kiartzis;A.G. Bakirtzis;J.B. Theocharis;G. Tsagas

  • Neural network observer for induction motor control

    J. Theocharis;V. Petridis

  • Subject Recognition Based on Ground Reaction Force Measurements of Gait Signals

    S.P. Moustakidis;J.B. Theocharis;G. Giakas

  • Short-term load forecasting in an autonomous power system using artificial neural networks

    S.J. Kiartzis;C.E. Zoumas;J.B. Theocharis;A.G. Bakirtzis

  • A high-order recurrent neuro-fuzzy system with internal dynamics: Application to the adaptive noise cancellation

    J. B. Theocharis

  • A Genetic Fuzzy-Rule-Based Classifier for Land Cover Classification From Hyperspectral Imagery

    D. G. Stavrakoudis;G. N. Galidaki;I. Z. Gitas;J. B. Theocharis

  • A memory-based learning approach utilizing combined spectral sources and geographical proximity for improved VIS-NIR-SWIR soil properties estimation

    Nikolaos Tziolas;Nikolaos Tsakiridis;Eyal Ben-Dor;John Theocharis

Frequent Co-Authors

Vassilios Petridis
Vassilios Petridis Aristotle University of Thessaloniki
Anastasios G. Bakirtzis
Anastasios G. Bakirtzis Aristotle University of Thessaloniki
Eyal Ben-Dor
Eyal Ben-Dor Tel Aviv University
George Vachtsevanos
George Vachtsevanos Georgia Institute of Technology
George A. Rovithakis
George A. Rovithakis Aristotle University of Thessaloniki
P.S. Dokopoulos
P.S. Dokopoulos Aristotle University of Thessaloniki
Panos Panagos
Panos Panagos European Commission
Periklis Chatzimisios
Periklis Chatzimisios International Hellenic University
Anastasios I. Zouboulis
Anastasios I. Zouboulis Aristotle University of Thessaloniki

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