World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
44
Citations
11450
World Ranking
3657
National Ranking
201

Marco Rivera 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 Marco Rivera 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: 462 publications — 81st percentile

81% of scientists in this discipline score the same or lower.

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

Marco Rivera 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 Marco Rivera 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: 44 D-Index — 47th percentile

47% of scientists in this discipline score the same or lower.

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

Overview

Marco Rivera is affiliated with the University of Nottingham in the United Kingdom. Their primary field of study is Engineering, with a significant focus on Electrical and Electronic Engineering, along with Control and Systems Engineering. They also contribute to subfields including Renewable Energy, Sustainability and the Environment, Automotive Engineering, and Computer Networks and Communications.

Rivera's research concentrates on several main topics, including:

  • Multilevel Inverters and Converters
  • Advanced DC-DC Converters
  • Microgrid Control and Optimization
  • Silicon Carbide Semiconductor Technologies
  • Sensorless Control of Electric Motors
  • Photovoltaic System Optimization Techniques
  • Advanced Battery Technologies Research

Their recent publications cover various aspects of power electronics and motor drive systems, with notable papers such as:

  • "A Low-Complexity Optimal Switching Time-Modulated Model-Predictive Control for PMSM With Three-Level NPC Converter" (2020), published in IEEE Transactions on Transportation Electrification
  • "A Reduced Single-Phase Switched-Diode Cascaded Multilevel Inverter" (2020), published in IEEE Journal of Emerging and Selected Topics in Power Electronics
  • "A Novel Modulated Model Predictive Control Applied to Six-Phase Induction Motor Drives" (2020), published in IEEE Transactions on Industrial Electronics
  • "Trends and Challenges in Multi-Level Inverter with Reduced Switches" (2021), published in Electronics
  • "Predictive Control for Microgrid Applications: A Review Study" (2020), published in Energies

Rivera collaborates frequently with a group of coauthors, including Patrick Wheeler, Javier Muñoz, Diego Rojas, Jaime Rohten, and Sérgio Toledo.

They have contributed extensively to several publication venues, reflecting their engagement with the academic community in electrical and control engineering. Key venues where Rivera has published include:

  • 2021 IEEE CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON)
  • 2022 IEEE International Conference on Automation/XXV Congress of the Chilean Association of Automatic Control (ICA-ACCA)
  • 2021 IEEE International Conference on Automation/XXIV Congress of the Chilean Association of Automatic Control (ICA-ACCA)
  • Energies
  • IEEE Access

In addition to journal and conference publications, Rivera authored a book titled Practical Guide to Machine Learning, NLP, and Generative AI: Libraries, Algorithms, and Applications, published in 2024 by River Publishers eBooks.

Best Publications

  • Model Predictive Control for Power Converters and Drives: Advances and Trends

    Sergio Vazquez;Jose Rodriguez;Marco Rivera;Leopoldo G. Franquelo

  • A Review of Control and Modulation Methods for Matrix Converters

    Jose Rodriguez;Marco Rivera;Johan W. Kolar;Patrick W. Wheeler

  • Improved Active Power Filter Performance for Renewable Power Generation Systems

    Pablo Acuna;Luis Moran;Marco Rivera;Juan Dixon

  • Finite-Set Model-Predictive Control Strategies for a 3L-NPC Inverter Operating With Fixed Switching Frequency

    Felipe Donoso;Andres Mora;Roberto Cardenas;Alejandro Angulo

  • Model Predictive Current Control of Two-Level Four-Leg Inverters—Part I: Concept, Algorithm, and Simulation Analysis

    V. Yaramasu;M. Rivera;Bin Wu;J. Rodriguez

  • Model Predictive Approach for a Simple and Effective Load Voltage Control of Four-Leg Inverter With an Output $LC$ Filter

    Venkata Yaramasu;Marco Rivera;Mehdi Narimani;Bin Wu

  • Multiobjective Switching State Selector for Finite-States Model Predictive Control Based on Fuzzy Decision Making in a Matrix Converter

    F. Villarroel;J. R. Espinoza;C. A. Rojas;J. Rodriguez

  • Current Control for an Indirect Matrix Converter With Filter Resonance Mitigation

    M. Rivera;J. Rodriguez;Bin Wu;J. R. Espinoza

  • Digital Predictive Current Control of a Three-Phase Four-Leg Inverter

    M. Rivera;V. Yaramasu;Ana Llor;J. Rodriguez

  • Predictive control of an indirect matrix converter

    P. Correa;J. Rodriguez;M. Rivera;J.R. Espinoza

  • Predictive Current Control With Input Filter Resonance Mitigation for a Direct Matrix Converter

    M. Rivera;C. Rojas;J. Rodríguez;P. Wheeler

  • A Comparative Assessment of Model Predictive Current Control and Space Vector Modulation in a Direct Matrix Converter

    M. Rivera;A. Wilson;C. A. Rojas;J. Rodriguez

  • A Single-Objective Predictive Control Method for a Multivariable Single-Phase Three-Level NPC Converter-Based Active Power Filter

    Pablo Acuna;Luis Moran;Marco Rivera;Ricardo Aguilera

  • Model Predictive Current Control of Two-Level Four-Leg Inverters—Part II: Experimental Implementation and Validation

    M. Rivera;V. Yaramasu;J. Rodriguez;Bin Wu

  • Stabilization of unstable steady states and periodic orbits in an electrochemical system using delayed-feedback control.

    P. Parmananda;R. Madrigal;M. Rivera;L. Nyikos

  • A New Power Conversion System for Megawatt PMSG Wind Turbines Using Four-Level Converters and a Simple Control Scheme Based on Two-Step Model Predictive Strategy—Part II: Simulation and Experimental Analysis

    Venkata Yaramasu;Bin Wu;Marco Rivera;Jose Rodriguez

  • Predictive Control of an Induction Machine Fed by a Matrix Converter With Increased Efficiency and Reduced Common-Mode Voltage

    Rene Vargas;Jose Rodriguez;Christian A. Rojas;Marco Rivera

  • A Computationally Efficient Lookup Table Based FCS-MPC for PMSM Drives Fed by Matrix Converters

    Mohsen Siami;Davood Arab Khaburi;Marco Rivera;Jose Rodriguez

  • Instantaneous Reactive Power Minimization and Current Control for an Indirect Matrix Converter Under a Distorted AC Supply

    M. Rivera;J. Rodriguez;J. R. Espinoza;H. Abu-Rub

  • Predictive Torque Control of a Multidrive System Fed by a Dual Indirect Matrix Converter

    Miguel Lopez;Jose Rodriguez;Cesar Silva;Marco Rivera

Frequent Co-Authors

Patrick Wheeler
Patrick Wheeler University of Nottingham
Jose Rodriguez
Jose Rodriguez San Sebastián University
Jose Espinoza
Jose Espinoza University of Concepción
Bin Wu
Bin Wu Toronto Metropolitan University
Venkata Yaramasu
Venkata Yaramasu Northern Arizona University
Ruben Pena
Ruben Pena University of Concepción
Pericle Zanchetta
Pericle Zanchetta University of Nottingham
Tomislav Dragicevic
Tomislav Dragicevic Technical University of Denmark
Jon Clare
Jon Clare University of Nottingham

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Related Online Degrees & Career Pathways

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Additionally, those interested in training and development within engineering firms might explore pathways through the best online master’s for teaching. This specialization can support careers in creating and delivering technical training programs for engineering teams.

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