World's Best Scientists 2026 revealed!

D-Index & Metrics

Electronics and Electrical Engineering

D-Index
35
Citations
6449
World Ranking
5487
National Ranking
1883

Daniel J. Trudnowski 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 J. Trudnowski 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: 123 publications — 8th percentile

8% of scientists in this discipline score the same or lower.

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

Daniel J. Trudnowski 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 J. Trudnowski 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: 35 D-Index — 21st percentile

21% 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

  • 2010 - IEEE Fellow For contributions to algorithms for characterizing power-system small-signal stability properties

Overview

Daniel J. Trudnowski is affiliated with Montana Tech of the University of Montana in the United States. Their research primarily focuses on engineering with specific expertise in electrical and electronic engineering, control and systems engineering, and related subfields.

The main topics of their work include:

  • Power System Optimization and Stability
  • Power Systems Fault Detection
  • HVDC Systems and Fault Protection
  • Microgrid Control and Optimization
  • Optimal Power Flow Distribution
  • Smart Grid Security and Resilience
  • Frequency Control in Power Systems

The scientist has authored several papers across notable publication venues. Some of the recent papers are:

  • Multi-Loop Transient Stability Control via Power Modulation From Energy Storage Devices, 2021, IEEE Transactions on Power Systems
  • Real Power Modulation Strategies for Transient Stability Control, 2022, IEEE Access
  • A Strategy for Forced Oscillation Suppression, 2020, IEEE Transactions on Power Systems
  • Impacts of swinging door lossy compression of synchrophasor data, 2020, International Journal of Electrical Power & Energy Systems
  • Feedback Control Strategy for Transient Stability Application, 2022, Energies

Frequent coauthors working with Daniel J. Trudnowski include:

  • Ryan Elliott
  • G.J. Rogers
  • Felipe Wilches-Bernal
  • Denis Osipov
  • Joe H. Chow

Publication venues where the scientist has multiple contributions are:

  • IEEE Transactions on Power Systems
  • IEEE Access
  • International Journal of Electrical Power & Energy Systems
  • Energies
  • 2022 IEEE Power & Energy Society General Meeting (PESGM)

In addition to journal articles, they have contributed to book publications, including a forthcoming work titled Power System Oscillations published by Springer Nature, expected in 2025.

Daniel J. Trudnowski's research is grounded in developing advanced methods for power system stability and control, including transient stability, oscillation suppression, and power modulation strategies. Their work also extends into data compression techniques for synchrophasor measurements.

Recognition for their contributions includes the IEEE Fellow award received in 2010 for work on algorithms characterizing power-system small-signal stability properties.

Best Publications

  • Making Prony analysis more accurate using multiple signals

    D.J. Trudnowski;J.M. Johnson;J.F. Hauer

  • Initial results in electromechanical mode identification from ambient data

    J.W. Pierre;D.J. Trudnowski;M.K. Donnelly

  • Use of ARMA block processing for estimating stationary low-frequency electromechanical modes of power systems

    R. W. Wies;J. W. Pierre;D. J. Trudnowski

  • Performance of three mode-meter block-processing algorithms for automated dynamic stability assessment

    D. Trudnowski;J. Pierre;Ning Zhou;J. Hauer

  • Fixed-speed wind-generator and wind-park modeling for transient stability studies

    D.J. Trudnowski;A. Gentile;J.M. Khan;E.M. Petritz

  • Electromechanical Mode Online Estimation Using Regularized Robust RLS Methods

    Ning Zhou;D.J. Trudnowski;J.W. Pierre;W.A. Mittelstadt

  • Impacts of the distributed utility on transmission system stability

    M.K. Donnelly;J.E. Dagle;D.J. Trudnowski;G.J. Rogers

  • An application of Prony methods in PSS design for multimachine systems

    D.J. Trudnowski;J.R. Smith;T.A. Short;D.A. Pierre

  • Robust RLS Methods for Online Estimation of Power System Electromechanical Modes

    Ning Zhou;J.W. Pierre;D.J. Trudnowski;R.T. Guttromson

  • Estimating Electromechanical Mode Shape From Synchrophasor Measurements

    D.J. Trudnowski

  • Transfer function identification in power system applications

    J.R. Smith;F. Fatehi;C.S. Woods;J.F. Hauer

  • A Perspective on WAMS Analysis Tools for Tracking of Oscillatory Dynamics

    A.J.F. Hauer;D.J. Trudnowski;J.G. DeSteese

  • Identification of Electromechanical Modes in Power Systems

    Juan Sanchez-Gasca;Daniel Trudnowski;Emilio Barocio;John Hauer

  • Use of the WECC WAMS in Wide-Area Probing Tests for Validation of System Performance and Modeling

    J.F. Hauer;W.A. Mittelstadt;K.E. Martin;J.W. Burns

  • A stepwise regression method for estimating dominant electromechanical modes

    Ning Zhou;J. Pierre;D. Trudnowski

  • PDCI damping control analysis for the western North American power system

    Daniel Trudnowski;Dmitry Kosterev;John Undrill

  • Keeping an eye on power system dynamics

    Unknown

  • Mode shape estimation algorithms under ambient conditions: A comparative review

    Luke Dosiek;Ning Zhou;John W. Pierre;Zhenyu Huang

  • Application of ambient analysis techniques for the estimation of electromechanical oscillations from measured PMU data in four different power systems

    Luigi Vanfretti;Luke Dosiek;John W. Pierre;Daniel Trudnowski

  • Overview of algorithms for estimating swing modes from measured responses

    D. J. Trudnowski;J. W. Pierre

  • Use of least mean squares (LMS) adaptive filtering technique for estimating low-frequency electromechanical modes in power systems

    R.W. Wies;J.W. Pierre;D.J. Trudnowski

  • Probing Signal Design for Power System Identification

    John W Pierre;Ning Zhou;Francis K Tuffner;John F Hauer

Frequent Co-Authors

Zhenyu Huang
Zhenyu Huang Pacific Northwest National Laboratory
Joe H. Chow
Joe H. Chow Rensselaer Polytechnic Institute
Bikash C. Pal
Bikash C. Pal Imperial College London
Kjetil Uhlen
Kjetil Uhlen Norwegian University of Science and Technology
Innocent Kamwa
Innocent Kamwa Université Laval
Jacob Østergaard
Jacob Østergaard Technical University of Denmark
Claudio A. Canizares
Claudio A. Canizares University of Waterloo
Vijay Vittal
Vijay Vittal Arizona State University
David P. Chassin
David P. Chassin SLAC National Accelerator Laboratory

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