World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
35
Citations
18584
World Ranking
8844
National Ranking
2453

Eric A. Wan publication distribution in Engineering and Technology in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Engineering and Technology in 2026. The highlighted bar marks where Eric A. Wan sits on this spectrum.

38–47 publications: 20 scientists 48–57 publications: 35 scientists 58–67 publications: 96 scientists 68–77 publications: 135 scientists 78–87 publications: 190 scientists 88–97 publications: 259 scientists 98–107 publications: 283 scientists 108–117 publications: 369 scientists 118–127 publications: 341 scientists 128–137 publications: 386 scientists 138–147 publications: 372 scientists 148–157 publications: 457 scientists 158–167 publications: 415 scientists 168–177 publications: 407 scientists 178–187 publications: 421 scientists 188–197 publications: 378 scientists 198–207 publications: 403 scientists 208–217 publications: 317 scientists 218–227 publications: 346 scientists 228–237 publications: 321 scientists 238–247 publications: 260 scientists 248–257 publications: 280 scientists 258–267 publications: 240 scientists 268–277 publications: 214 scientists 278–287 publications: 242 scientists 288–297 publications: 203 scientists 298–307 publications: 166 scientists 308–317 publications: 154 scientists 318–327 publications: 175 scientists 328–337 publications: 159 scientists 338–347 publications: 99 scientists 348–357 publications: 131 scientists 358–367 publications: 106 scientists 368–377 publications: 118 scientists 378–387 publications: 97 scientists 388–397 publications: 108 scientists 398–407 publications: 82 scientists 408–417 publications: 71 scientists 418–427 publications: 64 scientists 428–437 publications: 55 scientists 438–447 publications: 54 scientists 448–457 publications: 60 scientists 458–467 publications: 47 scientists 468–477 publications: 40 scientists 478–487 publications: 30 scientists 488–497 publications: 29 scientists 498–507 publications: 38 scientists 508–517 publications: 40 scientists 518–527 publications: 32 scientists 528–537 publications: 23 scientists 538–547 publications: 28 scientists 548–557 publications: 23 scientists 558–567 publications: 19 scientists 568–577 publications: 16 scientists 578–587 publications: 17 scientists 588–597 publications: 18 scientists 598–607 publications: 22 scientists 608–617 publications: 15 scientists 618–627 publications: 9 scientists 628–637 publications: 11 scientists 638–647 publications: 21 scientists 648–657 publications: 12 scientists 658–667 publications: 9 scientists 668–677 publications: 11 scientists 678–687 publications: 9 scientists 688–697 publications: 6 scientists 698–707 publications: 14 scientists 708–717 publications: 7 scientists 718–727 publications: 8 scientists 728–737 publications: 10 scientists 738–747 publications: 9 scientists 748–757 publications: 5 scientists 758–767 publications: 5 scientists 768–777 publications: 11 scientists 778–787 publications: 7 scientists 788–797 publications: 2 scientists 798–803 publications: 4 scientists 804+ publications: 100 scientists
38 publications 804+

This scientist: 80 publications — 3rd percentile

3% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 804 publications or more.

Eric A. Wan D-index placement in Engineering and Technology in 2026

The chart shows the D-index (discipline H-index) distribution of Engineering and Technology scientists ranked by Research.com in 2026. The highlighted bar marks where Eric A. Wan sits on this spectrum.

30 D-Index: 59 scientists 31 D-Index: 114 scientists 32 D-Index: 129 scientists 33 D-Index: 189 scientists 34 D-Index: 200 scientists 35 D-Index: 262 scientists 36 D-Index: 311 scientists 37 D-Index: 312 scientists 38 D-Index: 350 scientists 39 D-Index: 385 scientists 40 D-Index: 348 scientists 41 D-Index: 362 scientists 42 D-Index: 426 scientists 43 D-Index: 380 scientists 44 D-Index: 310 scientists 45 D-Index: 341 scientists 46 D-Index: 301 scientists 47 D-Index: 306 scientists 48 D-Index: 271 scientists 49 D-Index: 246 scientists 50 D-Index: 210 scientists 51 D-Index: 253 scientists 52 D-Index: 213 scientists 53 D-Index: 221 scientists 54 D-Index: 195 scientists 55 D-Index: 186 scientists 56 D-Index: 170 scientists 57 D-Index: 167 scientists 58 D-Index: 166 scientists 59 D-Index: 144 scientists 60 D-Index: 152 scientists 61 D-Index: 141 scientists 62 D-Index: 138 scientists 63 D-Index: 131 scientists 64 D-Index: 118 scientists 65 D-Index: 114 scientists 66 D-Index: 119 scientists 67 D-Index: 95 scientists 68 D-Index: 87 scientists 69 D-Index: 77 scientists 70 D-Index: 89 scientists 71 D-Index: 69 scientists 72 D-Index: 54 scientists 73 D-Index: 46 scientists 74 D-Index: 55 scientists 75 D-Index: 54 scientists 76 D-Index: 49 scientists 77 D-Index: 53 scientists 78 D-Index: 46 scientists 79 D-Index: 28 scientists 80 D-Index: 39 scientists 81 D-Index: 36 scientists 82 D-Index: 24 scientists 83 D-Index: 26 scientists 84 D-Index: 36 scientists 85 D-Index: 18 scientists 86 D-Index: 25 scientists 87 D-Index: 19 scientists 88 D-Index: 26 scientists 89 D-Index: 27 scientists 90 D-Index: 23 scientists 91 D-Index: 15 scientists 92 D-Index: 12 scientists 93 D-Index: 9 scientists 94 D-Index: 15 scientists 95 D-Index: 10 scientists 96 D-Index: 13 scientists 97 D-Index: 13 scientists 98 D-Index: 9 scientists 99 D-Index: 7 scientists 100 D-Index: 7 scientists 101 D-Index: 8 scientists 102 D-Index: 7 scientists 103 D-Index: 7 scientists 104 D-Index: 9 scientists 105 D-Index: 6 scientists 106 D-Index: 9 scientists 107+ D-Index: 99 scientists
30 D-Index 107+

This scientist: 35 D-Index — 10th percentile

10% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 107 D-Index or more.

Overview

Eric A. Wan is a researcher affiliated with Portland State University in the United States, contributing primarily within the fields of Engineering and Medicine. Their scholarly work encompasses specialties including Physical Therapy, Sports Therapy and Rehabilitation, Endocrinology, Diabetes and Metabolism, Electrical and Electronic Engineering, Ocean Engineering, and Biomedical Engineering.

Their research addresses topics such as Balance, Gait, and Falls Prevention, Diabetic Foot Ulcer Assessment and Management, Indoor and Outdoor Localization Technologies, Geophysical Methods and Applications, Microwave Imaging and Scattering Analysis, Ultrasonics and Acoustic Wave Propagation, and Cerebral Palsy and Movement Disorders.

Eric A. Wan's recent publications include:

  • Automated Detection of Real-World Falls: Modeled From People With Multiple Sclerosis (2020), IEEE Journal of Biomedical and Health Informatics
  • A pipeline for enhanced multimodal 2D imaging of concrete structures (2021), Materials and Structures
  • Comparing fall detection methods in people with multiple sclerosis: A prospective observational cohort study (2021), Multiple Sclerosis and Related Disorders
  • Design and Experiment of a Fertilization Rotation Speed Control System Based on Radar Speed Feedback (2025), Processes
  • Design and Experiment of a Multi-Row Spiral Quantitative Fertilizer Distributor (2025), Processes

They have collaborated frequently with coauthors including Clara Mosquera-Lopez, Jonathon Folsom, Andrea Hildebrand, Michelle Cameron, and Peter G. Jacobs.

Eric A. Wan's work appears across several publication venues, notably:

  • Processes
  • IEEE Journal of Biomedical and Health Informatics
  • Materials and Structures
  • Multiple Sclerosis and Related Disorders

Best Publications

  • The unscented Kalman filter for nonlinear estimation

    E.A. Wan;R. Van Der Merwe

  • The Unscented Particle Filter

    Rudolph van der Merwe;Arnaud Doucet;Nando de Freitas;Eric A. Wan

  • The square-root unscented Kalman filter for state and parameter-estimation

    R. Van der Merwe;E.A. Wan

  • The Unscented Kalman Filter

    Eric A. Wan;Rudolph van der Merwe

  • Sigma-point kalman filters for probabilistic inference in dynamic state-space models

    Rudolph Van Der Merwe;Eric A. Wan

  • Sigma-Point Kalman Filters for Nonlinear Estimation and Sensor-Fusion: Applications to Integrated Navigation

    Rudolph van der Merwe;Eric Wan;Simon Julier

  • Sigma-Point Kalman Filters for Nonlinear Estimation and Sensor Fusion: Applications to Integrated Navigation

    R van der Merwe;E Wan;SJ Julier

  • Neural network classification: a Bayesian interpretation

    E.A. Wan

  • RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers

    A.S. Paul;E.A. Wan

  • Dual Estimation and the Unscented Transformation

    Eric A. Wan;Rudolph van der Merwe;Alex T. Nelson

  • Dual Extended Kalman Filter Methods

    Eric A. Wan;Alex T. Nelson

  • Sigma-Point Kalman Filters for Integrated Navigation

    Rudolph van der Merwe;Eric A. Wan

  • Temporal backpropagation for FIR neural networks

    E.A. Wan

  • Gaussian mixture sigma-point particle filters for sequential probabilistic inference in dynamic state-space models

    R. van der Merwe;E. Wan

  • Efficient derivative-free Kalman filters for online learning.

    Rudolph van der Merwe;Eric A. Wan

  • Finite impulse response neural networks with applications in time series prediction

    Eric Andrew Wan

  • Dual Kalman Filtering Methods for Nonlinear Prediction, Smoothing and Estimation

    Eric A. Wan;Alex T. Nelson

  • Neural dual extended Kalman filtering: applications in speech enhancement and monaural blind signal separation

    E.A. Wan;A.T. Nelson

  • Navigation system applications of sigma-point Kalman filters for nonlinear estimation and sensor fusion

    Rudolph van der Merwe;Eric A. Wan;Simon J. Julier

  • Adjoint LMS: an efficient alternative to the filtered-x LMS and multiple error LMS algorithms

    E.A. Wan

  • Nonlinear estimation and modeling of noisy time series by dual kalman filtering methods

    Eric A. Wan;Alex Tremain Nelson

Frequent Co-Authors

Francoise Beaufays
Francoise Beaufays Google (United States)
Hynek Hermansky
Hynek Hermansky Johns Hopkins University
Simon Julier
Simon Julier University College London
Bernard Widrow
Bernard Widrow Stanford University
James McNames
James McNames Portland State University
Arnaud Doucet
Arnaud Doucet University of Oxford
Nando de Freitas
Nando de Freitas DeepMind (United Kingdom)
Jeffrey Kaye
Jeffrey Kaye Oregon Health & Science University
Ah Chung Tsoi
Ah Chung Tsoi University of Wollongong
Giovanni Pellacani
Giovanni Pellacani Sapienza University of Rome

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