World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
41
Citations
6516
World Ranking
8898
National Ranking
132

Sergio Toral 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 Sergio Toral 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: 228 publications — 56th percentile

56% of scientists in this discipline score the same or lower.

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

Sergio Toral 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 Sergio Toral 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

Sergio Toral is affiliated with the University of Seville in Spain and has a research focus spanning computer science and engineering. Their work prominently intersects with artificial intelligence, computer vision and pattern recognition, ocean engineering, computer networks and communications, and water science and technology.

The scientist's research explores various main topics, including:

  • Robotic Path Planning Algorithms
  • Water Quality Monitoring Technologies
  • Reinforcement Learning in Robotics
  • Optimization and Search Problems
  • Water Resources Management and Optimization
  • Underwater Vehicles and Communication Systems
  • Digital Marketing and Social Media

Sergio Toral has contributed extensively to notable publication venues, with multiple pieces appearing in:

  • IEEE Access
  • Sensors
  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • Expert Systems with Applications

Among the recent papers authored or co-authored by Sergio Toral are:

  • A Multiagent Deep Reinforcement Learning Approach for Path Planning in Autonomous Surface Vehicles: The Ypacaraí Lake Patrolling Case (2021, IEEE Access)
  • A Comparison of Local Path Planning Techniques of Autonomous Surface Vehicles for Monitoring Applications: The Ypacarai Lake Case-study (2020, Sensors)
  • A Deep Reinforcement Learning Approach for the Patrolling Problem of Water Resources Through Autonomous Surface Vehicles: The Ypacarai Lake Case (2020, IEEE Access)
  • Prediction and Modelling Online Reviews Helpfulness Using 1D Convolutional Neural Networks (2022, Expert Systems with Applications)
  • A Bayesian Optimization Approach for Water Resources Monitoring Through an Autonomous Surface Vehicle: The Ypacarai Lake Case Study (2021, IEEE Access)

The scientist frequently collaborates with fellow researchers including Daniel Gutiérrez Reina, Samuel Yanes Luis, María del Rocío Martínez Torres, Federico Peralta, and Mario Arzamendia.

Best Publications

  • Speed Control of Five-Phase Induction Motors With Integrated Open-Phase Fault Operation Using Model-Based Predictive Current Control Techniques

    Hugo Guzman;Mario J. Duran;Federico Barrero;Blas Bogado

  • Post-visit and pre-visit tourist destination image through eWOM sentiment analysis and perceived helpfulness

    M. Rosario González-Rodríguez;Rocio Martínez-Torres;Sergio Toral

  • A survey on probabilistic broadcast schemes for wireless ad hoc networks

    D.G. Reina;S.L. Toral;P. Johnson;F. Barrero

  • Analysis of virtual communities supporting OSS projects using social network analysis

    S. L. Toral;M. R. Martínez-Torres;F. Barrero

  • A distributed PSO-based exploration algorithm for a UAV network assisting a disaster scenario

    J. Sánchez-García;D.G. Reina;S.L. Toral

  • A survey on multihop ad hoc networks for disaster response scenarios

    D. G. Reina;M. Askalani;S. L. Toral;F. Barrero

  • An empirical study of the driving forces behind online communities

    Sergio L. Toral;M. Rocío Martínez‐Torres;Federico Barrero;Francisco Cortés

  • A survey on unmanned aerial and aquatic vehicle multi-hop networks: Wireless communications, evaluation tools and applications

    J. Sánchez-García;J.M. García-Campos;M. Arzamendia;D.G. Reina

  • Comparative Analysis of Discontinuous and Continuous PWM Techniques in VSI-Fed Five-Phase Induction Motor

    J. Prieto;M. Jones;F. Barrero;E. Levi

  • Multi-phase current control using finite-state model-predictive control

    M.R. Arahal;F. Barrero;S. Toral;M. Duran

  • An Enhanced Background Estimation Algorithm for Vehicle Detection in Urban Traffic Scenes

    M Vargas;J M Milla;S L Toral;F Barrero

  • The Role of Ad Hoc Networks in the Internet of Things: A Case Scenario for Smart Environments

    Daniel G. Reina;Sergio L. Toral;Federico Barrero;Nik Bessis

  • A machine learning approach for the identification of the deceptive reviews in the hospitality sector using unique attributes and sentiment orientation

    M.R. Martinez-Torres;S.L. Toral

  • Comment on "Implementation of a Web-Based Educational Tool for Digital Signal Processing Teaching Using the Technological Acceptance Model

    S.L.T. Marin;F.J.B. Garcia;R.M. Torres;S.G. Vazquez

  • Identification of the Unique Attributes of Tourist Destinations from Online Reviews

    S. L. Toral;M. R. Martínez-Torres;M. R. Gonzalez-Rodriguez

  • SVM Procedure for $n$ -Phase VSI With Low Harmonic Distortion in the Overmodulation Region

    Joel Prieto;Federico Barrero;Mario J. Duran;Sergio Toral Marin

  • Stochastic pulse coded arithmetic

    S.L. Toral;J.M. Quero;L.G. Franquelo

  • A Learning Methodology Using Matlab/Simulink for Undergraduate Electrical Engineering Courses Attending to Learner Satisfaction Outcomes.

    Mario J. Durán;Sergio Gallardo;Sergio L. Toral;Rocío Martínez-Torres

  • Analysis of utility and use of a web-based tool for digital signal processing teaching by means of a technological acceptance model

    S. L. Toral;F. Barrero;M. R. Martínez-Torres

  • Modelling and assessing ad hoc networks in disaster scenarios

    Daniel Gutiérrez Reina;S. L. Toral;Federico Barrero;N. Bessis

  • Evaluation of Ad Hoc Networks in Disaster Scenarios

    D.G. Reina;Sergio L. Toral;Federico Barrero;Nik Bessis

  • Multi-subpopulation evolutionary algorithms for coverage deployment of UAV-networks

    D.G. Reina;H. Tawfik;S.L. Toral

Frequent Co-Authors

Federico Barrero
Federico Barrero University of Seville
Mario J. Duran
Mario J. Duran University of Malaga
Leopoldo G. Franquelo
Leopoldo G. Franquelo University of Seville
Nik Bessis
Nik Bessis Edge Hill University
Emil Levi
Emil Levi Liverpool John Moores University
Martin Jones
Martin Jones Liverpool John Moores University
Ciprian Dobre
Ciprian Dobre Polytechnic University of Bucharest
Khaled Shaalan
Khaled Shaalan British University in Dubai
Bernabé Dorronsoro
Bernabé Dorronsoro University of Cádiz
Teodoro Alamo
Teodoro Alamo University of Seville

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