World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
38
Citations
5592
World Ranking
4939
National Ranking
92

Carlos Ocampo-Martinez publication distribution in Electronics and Electrical Engineering in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Electronics and Electrical Engineering in 2026. The highlighted bar marks where Carlos Ocampo-Martinez sits on this spectrum.

34–53 publications: 24 scientists 54–73 publications: 52 scientists 74–93 publications: 114 scientists 94–113 publications: 203 scientists 114–133 publications: 269 scientists 134–153 publications: 355 scientists 154–173 publications: 403 scientists 174–193 publications: 445 scientists 194–213 publications: 430 scientists 214–233 publications: 431 scientists 234–253 publications: 399 scientists 254–273 publications: 366 scientists 274–293 publications: 335 scientists 294–313 publications: 300 scientists 314–333 publications: 276 scientists 334–353 publications: 250 scientists 354–373 publications: 214 scientists 374–393 publications: 187 scientists 394–413 publications: 152 scientists 414–433 publications: 169 scientists 434–453 publications: 147 scientists 454–473 publications: 111 scientists 474–493 publications: 117 scientists 494–513 publications: 103 scientists 514–533 publications: 99 scientists 534–553 publications: 92 scientists 554–573 publications: 75 scientists 574–593 publications: 58 scientists 594–613 publications: 69 scientists 614–633 publications: 50 scientists 634–653 publications: 62 scientists 654–673 publications: 54 scientists 674–693 publications: 44 scientists 694–713 publications: 37 scientists 714–733 publications: 28 scientists 734–753 publications: 26 scientists 754–773 publications: 26 scientists 774–793 publications: 19 scientists 794–813 publications: 23 scientists 814–833 publications: 20 scientists 834–853 publications: 16 scientists 854–873 publications: 20 scientists 874–893 publications: 11 scientists 894–913 publications: 11 scientists 914–933 publications: 16 scientists 934–953 publications: 13 scientists 954–973 publications: 10 scientists 974–993 publications: 11 scientists 994–1,013 publications: 9 scientists 1,014–1,033 publications: 9 scientists 1,034–1,053 publications: 10 scientists 1,054–1,064 publications: 6 scientists 1,065+ publications: 99 scientists
34 publications 1,065+

This scientist: 272 publications — 51st percentile

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

The last bar groups every scientist with 1,065 publications or more.

Carlos Ocampo-Martinez D-index placement in Electronics and Electrical Engineering in 2026

The chart shows the D-index (discipline H-index) distribution of Electronics and Electrical Engineering scientists ranked by Research.com in 2026. The highlighted bar marks where Carlos Ocampo-Martinez sits on this spectrum.

30 D-Index: 178 scientists 31 D-Index: 257 scientists 32 D-Index: 263 scientists 33 D-Index: 262 scientists 34 D-Index: 244 scientists 35 D-Index: 236 scientists 36 D-Index: 211 scientists 37 D-Index: 220 scientists 38 D-Index: 214 scientists 39 D-Index: 214 scientists 40 D-Index: 205 scientists 41 D-Index: 187 scientists 42 D-Index: 194 scientists 43 D-Index: 201 scientists 44 D-Index: 155 scientists 45 D-Index: 189 scientists 46 D-Index: 148 scientists 47 D-Index: 160 scientists 48 D-Index: 134 scientists 49 D-Index: 130 scientists 50 D-Index: 141 scientists 51 D-Index: 156 scientists 52 D-Index: 108 scientists 53 D-Index: 130 scientists 54 D-Index: 112 scientists 55 D-Index: 97 scientists 56 D-Index: 111 scientists 57 D-Index: 102 scientists 58 D-Index: 108 scientists 59 D-Index: 120 scientists 60 D-Index: 103 scientists 61 D-Index: 93 scientists 62 D-Index: 92 scientists 63 D-Index: 74 scientists 64 D-Index: 77 scientists 65 D-Index: 73 scientists 66 D-Index: 64 scientists 67 D-Index: 69 scientists 68 D-Index: 60 scientists 69 D-Index: 39 scientists 70 D-Index: 57 scientists 71 D-Index: 59 scientists 72 D-Index: 46 scientists 73 D-Index: 49 scientists 74 D-Index: 38 scientists 75 D-Index: 35 scientists 76 D-Index: 32 scientists 77 D-Index: 35 scientists 78 D-Index: 31 scientists 79 D-Index: 22 scientists 80 D-Index: 34 scientists 81 D-Index: 31 scientists 82 D-Index: 34 scientists 83 D-Index: 23 scientists 84 D-Index: 18 scientists 85 D-Index: 30 scientists 86 D-Index: 19 scientists 87 D-Index: 19 scientists 88 D-Index: 20 scientists 89 D-Index: 8 scientists 90 D-Index: 17 scientists 91 D-Index: 7 scientists 92 D-Index: 14 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 12 scientists 97 D-Index: 10 scientists 98 D-Index: 10 scientists 99 D-Index: 12 scientists 100 D-Index: 16 scientists 101 D-Index: 5 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 8 scientists 105 D-Index: 9 scientists 106 D-Index: 13 scientists 107 D-Index: 4 scientists 108 D-Index: 5 scientists 109 D-Index: 10 scientists 110 D-Index: 8 scientists 111+ D-Index: 96 scientists
30 D-Index 111+

This scientist: 38 D-Index — 30th percentile

30% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 111 D-Index or more.

Best Publications

  • Modeling and real-time control of urban drainage systems: A review☆

    L. García;J. Barreiro-Gomez;J. Barreiro-Gomez;E. Escobar;D. Téllez

  • Application of predictive control strategies to the management of complex networks in the urban water cycle [Applications of Control]

    C. Ocampo-Martinez;V. Puig;G. Cembrano;J. Quevedo

  • Novel hybrid fuzzy-PID control scheme for air supply in PEM fuel-cell-based systems

    Zakaria Baroud;Mohammed Benmiloud;Atallah Benalia;Carlos Ocampo-Martinez

  • The Role of Population Games and Evolutionary Dynamics in Distributed Control Systems: The Advantages of Evolutionary Game Theory

    Nicanor Quijano;Carlos Ocampo-Martinez;Julian Barreiro-Gomez;German Obando

  • Chance-Constrained Model Predictive Control for Drinking Water Networks

    J.M. Grosso;C. Ocampo-Martínez;V. Puig;B. Joseph

  • Model Predictive Control of Wastewater Systems

    Carlos Ocampo-Martinez

  • Partitioning Approach oriented to the Decentralised Predictive Control of Large-Scale Systems

    Carlos Ocampo-Martinez;Samuele Bovo;Vicenç Puig

  • On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid

    P. Velarde;L. Valverde;Jose Maria Maestre;Carlos Ocampo-Martinez

  • Hierarchical and decentralised model predictive control of drinking water networks: Application to Barcelona case study

    Carlos Ocampo-Martinez;Davide Barcelli;Vicenç Puig;Alberto Bemporad

  • Design and implementation of LQR/LQG strategies for oxygen stoichiometry control in PEM fuel cells based systems

    Ali Niknezhadi;Miguel Allué-Fantova;Cristian Kunusch;Carlos Ocampo-Martínez

  • Nonlinear Model Predictive Control for Thermal Management in Plug-in Hybrid Electric Vehicles

    Jorge Lopez-Sanz;Carlos Ocampo-Martinez;Jesus Alvarez-Florez;Manuel Moreno-Eguilaz

  • Time-varying scheme for non-centralized model predictive control of large-scale systems

    Alfredo Núñez;Carlos Ocampo-Martinez;José María Maestre;Bart De Schutter

  • Energy efficiency in discrete-manufacturing systems: Insights, trends, and control strategies

    L C Jenny Diaz;Carlos Ocampo-Martinez

  • Objective Prioritization Using Lexicographic Minimizers for MPC of Sewer Networks

    C. Ocampo-Martinez;A. Ingimundarson;V. Puig;J. Quevedo

  • Data-driven energy prediction modeling for both energy efficiency and maintenance in smart manufacturing systems

    Miguel Angel Bermeo-Ayerbe;Carlos Ocampo-Martinez;Javier Diaz-Rozo

  • Improving water management efficiency by using optimization-based control strategies: the Barcelona case study

    Carlos Ocampo-Martinez;Vicenç Puig;Vicenç Puig;Gabriela Cembrano;Ramon Creus

  • A wind farm control strategy for power reserve maximization

    Sara Siniscalchi-Minna;Fernando D. Bianchi;Mikel De-Prada-Gil;Carlos Ocampo-Martinez

  • Operationally-Safe Peer-to-Peer Energy Trading in Distribution Grids: A Game-Theoretic Market-Clearing Mechanism.

    Giuseppe Belgioioso;Wicak Ananduta;Sergio Grammatico;Carlos Ocampo-Martinez

  • Tuning of predictive controllers for drinking water networked systems

    Rodrigo Toro;Carlos Ocampo-Martinez;Filip Logist;Jan F.M. Van Impe

  • Thermal Management in Plug-In Hybrid Electric Vehicles: A Real-Time Nonlinear Model Predictive Control Implementation

    J. Lopez-Sanz;Carlos Ocampo-Martinez;Jesus Alvarez-Florez;Manuel Moreno-Eguilaz

Frequent Co-Authors

Vicenç Puig
Vicenç Puig Universitat Politècnica de Catalunya
Sorin Olaru
Sorin Olaru CentraleSupélec
Joseba Quevedo
Joseba Quevedo Universitat Politècnica de Catalunya
Alberto Bemporad
Alberto Bemporad IMT Institute for Advanced Studies Lucca
Carlos Bordons
Carlos Bordons University of Seville
Angelia Nedic
Angelia Nedic Arizona State University
Silviu-Iulian Niculescu
Silviu-Iulian Niculescu CentraleSupélec
Rudy R. Negenborn
Rudy R. Negenborn Delft University of Technology
Hideaki Ishii
Hideaki Ishii Tokyo Institute of Technology

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Related Online Degrees & Career Pathways

For those interested in Electronics and Electrical Engineering, expanding your skill set through related online degrees can boost career prospects. A bachelor's degree in project management is a valuable complement, helping engineers manage complex projects and lead teams effectively.

Many professionals pursue education while working, making accelerated online bachelor degree programs accredited an ideal choice. These programs offer the flexibility to complete degrees faster without compromising on quality.

For advanced specialization, pathways such as an online masters in instructional design open opportunities in training, curriculum development, and technical education roles within engineering fields.

Additionally, exploring options at institutions featured in the list of competency-based colleges can help students demonstrate practical skills directly relevant to their careers. This competency-based approach ensures learning is tailored to individual pace and job experience.

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