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Daniel E. Quevedo

Daniel E. Quevedo

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
58
Citations
14480
World Ranking
1841
National Ranking
61

Daniel E. Quevedo 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 Daniel E. Quevedo 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: 332 publications — 64th percentile

64% of scientists in this discipline score the same or lower.

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

Daniel E. Quevedo 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 Daniel E. Quevedo 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: 58 D-Index — 74th percentile

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

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

Research.com Recognitions

  • 2021 - IEEE Fellow For contributions to optimal and model predictive control

Overview

Daniel E. Quevedo is affiliated with the Queensland University of Technology in Australia. Their research is primarily situated at the intersection of Engineering and Computer Science, with notable contributions in the subfields of Computer Networks and Communications, Control and Systems Engineering, Electrical and Electronic Engineering, Artificial Intelligence, and Management Science and Operations Research.

Their work addresses a range of topics, including:

  • Smart Grid Security and Resilience
  • Stability and Control of Uncertain Systems
  • Distributed Sensor Networks and Detection Algorithms
  • Age of Information Optimization
  • Security in Wireless Sensor Networks
  • Advanced Wireless Network Optimization
  • Wireless Communication Security Techniques

Their publication record is extensive, with significant contributions appearing in venues such as:

  • arXiv (Cornell University)
  • IEEE Transactions on Automatic Control
  • Automatica
  • IEEE Control Systems Letters
  • International Journal of Robust and Nonlinear Control

Recent papers authored or co-authored by Daniel E. Quevedo include:

  • "Encrypted Control for Networked Systems: An Illustrative Introduction and Current Challenges" (2021, IEEE Control Systems)
  • "On extended state estimation for nonlinear uncertain systems with round-robin protocol" (2022, Automatica)
  • "Remote State Estimation in the Presence of an Active Eavesdropper" (2020, IEEE Transactions on Automatic Control)
  • "Remote State Estimation With Smart Sensors Over Markov Fading Channels" (2021, IEEE Transactions on Automatic Control)
  • "Encryption scheduling for remote state estimation under an operation constraint" (2021, Automatica)

Frequent collaborators include:

  • Wanchun Liu
  • Yonghui Li
  • Branka Vucetic
  • Justin M. Kennedy
  • Alex S. Leong

In 2021, Daniel E. Quevedo was recognized as an IEEE Fellow for contributions to optimal and model predictive control.

Best Publications

  • Predictive Control in Power Electronics and Drives

    P. Cortes;M.P. Kazmierkowski;R.M. Kennel;D.E. Quevedo

  • Predictive Current Control Strategy With Imposed Load Current Spectrum

    P. Cortes;J. Rodriguez;D.E. Quevedo;C. Silva

  • Jamming Attacks on Remote State Estimation in Cyber-Physical Systems: A Game-Theoretic Approach

    Yuzhe Li;Ling Shi;Peng Cheng;Jiming Chen

  • Multistep Finite Control Set Model Predictive Control for Power Electronics

    Tobias Geyer;Daniel E. Quevedo

  • Predictive Optimal Switching Sequence Direct Power Control for Grid-Connected Power Converters

    Sergio Vazquez;Abraham Marquez;Ricardo Aguilera;Daniel Quevedo

  • A moving horizon approach to Networked Control system design

    G.C. Goodwin;H. Haimovich;D.E. Quevedo;J.S. Welsh

  • Performance of Multistep Finite Control Set Model Predictive Control for Power Electronics

    Tobias Geyer;Daniel E. Quevedo

  • SINR-Based DoS Attack on Remote State Estimation: A Game-Theoretic Approach

    Yuzhe Li;Daniel E. Quevedo;Subhrakanti Dey;Ling Shi

  • Model Predictive Control of an Asymmetric Flying Capacitor Converter

    P. Lezana;R. Aguilera;D.E. Quevedo

  • Model Predictive Control of an AFE Rectifier With Dynamic References

    D. E. Quevedo;R. P. Aguilera;M. A. Perez;P. Cortes

  • A multi-channel transmission schedule for remote state estimation under DoS attacks

    Kemi Ding;Yuzhe Li;Daniel E. Quevedo;Subhrakanti Dey

  • Finite-Control-Set Model Predictive Control With Improved Steady-State Performance

    R. P. Aguilera;P. Lezana;D. E. Quevedo

  • Input-to-State Stability of Packetized Predictive Control Over Unreliable Networks Affected by Packet-Dropouts

    D E Quevedo;Dragan Nešić

  • Predictive Control of Power Converters: Designs With Guaranteed Performance

    Ricardo P. Aguilera;Daniel E. Quevedo

  • Maximum Hands-Off Control: A Paradigm of Control Effort Minimization

    Masaaki Nagahara;Daniel E. Quevedo;Dragan Nesic

  • State Estimation Over Sensor Networks With Correlated Wireless Fading Channels

    D. E. Quevedo;A. Ahlen;K. H. Johansson

  • Finite constraint set receding horizon quadratic control

    Daniel E. Quevedo;Graham C. Goodwin;José A. De Doná

  • On Kalman filtering over fading wireless channels with controlled transmission powers

    Daniel E. Quevedo;Anders AhléN;Alex S. Leong;Subhrakanti Dey

  • Brief paper: Control system design subject to SNR constraints

    Eduardo I. Silva;Graham C. Goodwin;Daniel E. Quevedo

  • Deep reinforcement learning for wireless sensor scheduling in cyber-physical systems

    Alex S. Leong;Arunselvan Ramaswamy;Daniel E. Quevedo;Holger Karl

  • Brief paper: Architectures and coder design for networked control systems

    Graham C. Goodwin;Daniel E. Quevedo;Eduardo I. Silva

Frequent Co-Authors

Graham C. Goodwin
Graham C. Goodwin University of Newcastle Australia
Subhrakanti Dey
Subhrakanti Dey Uppsala University
Ling Shi
Ling Shi Hong Kong University of Science and Technology
Ricardo P. Aguilera
Ricardo P. Aguilera University of Technology Sydney
Vijay Gupta
Vijay Gupta Purdue University West Lafayette
Dragan Nesic
Dragan Nesic University of Melbourne
Tobias Geyer
Tobias Geyer ABB (Switzerland)
Karl Henrik Johansson
Karl Henrik Johansson Royal Institute of Technology
Pablo Lezana
Pablo Lezana Valparaiso University
Vincent K. N. Lau
Vincent K. N. Lau Hong Kong University of Science and Technology

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