World's Best Scientists 2026 revealed!

D-Index & Metrics

Environmental Sciences

D-Index
41
Citations
6329
World Ranking
7728
National Ranking
348

William W. Hsieh publication distribution in Environmental Sciences in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Environmental Sciences in 2026. The highlighted bar marks where William W. Hsieh sits on this spectrum.

41–50 publications: 21 scientists 51–60 publications: 62 scientists 61–70 publications: 133 scientists 71–80 publications: 257 scientists 81–90 publications: 361 scientists 91–100 publications: 440 scientists 101–110 publications: 492 scientists 111–120 publications: 541 scientists 121–130 publications: 617 scientists 131–140 publications: 544 scientists 141–150 publications: 541 scientists 151–160 publications: 539 scientists 161–170 publications: 444 scientists 171–180 publications: 444 scientists 181–190 publications: 400 scientists 191–200 publications: 377 scientists 201–210 publications: 318 scientists 211–220 publications: 283 scientists 221–230 publications: 263 scientists 231–240 publications: 220 scientists 241–250 publications: 217 scientists 251–260 publications: 180 scientists 261–270 publications: 181 scientists 271–280 publications: 155 scientists 281–290 publications: 130 scientists 291–300 publications: 127 scientists 301–310 publications: 130 scientists 311–320 publications: 85 scientists 321–330 publications: 106 scientists 331–340 publications: 80 scientists 341–350 publications: 83 scientists 351–360 publications: 75 scientists 361–370 publications: 69 scientists 371–380 publications: 52 scientists 381–390 publications: 54 scientists 391–400 publications: 56 scientists 401–410 publications: 44 scientists 411–420 publications: 40 scientists 421–430 publications: 36 scientists 431–440 publications: 25 scientists 441–450 publications: 25 scientists 451–460 publications: 32 scientists 461–470 publications: 29 scientists 471–480 publications: 21 scientists 481–490 publications: 26 scientists 491–500 publications: 25 scientists 501–510 publications: 17 scientists 511–520 publications: 18 scientists 521–530 publications: 15 scientists 531–540 publications: 22 scientists 541–550 publications: 12 scientists 551–560 publications: 15 scientists 561–570 publications: 11 scientists 571–580 publications: 19 scientists 581–590 publications: 9 scientists 591–600 publications: 9 scientists 601–610 publications: 7 scientists 611–620 publications: 11 scientists 621–630 publications: 5 scientists 631–640 publications: 5 scientists 641–650 publications: 6 scientists 651–660 publications: 3 scientists 661–670 publications: 3 scientists 671–680 publications: 4 scientists 681–686 publications: 3 scientists 687+ publications: 100 scientists
41 publications 687+

This scientist: 137 publications — 34th percentile

34% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 687 publications or more.

William W. Hsieh D-index placement in Environmental Sciences in 2026

The chart shows the D-index (discipline H-index) distribution of Environmental Sciences scientists ranked by Research.com in 2026. The highlighted bar marks where William W. Hsieh sits on this spectrum.

30 D-Index: 12 scientists 31 D-Index: 26 scientists 32 D-Index: 51 scientists 33 D-Index: 88 scientists 34 D-Index: 123 scientists 35 D-Index: 163 scientists 36 D-Index: 206 scientists 37 D-Index: 267 scientists 38 D-Index: 265 scientists 39 D-Index: 275 scientists 40 D-Index: 321 scientists 41 D-Index: 343 scientists 42 D-Index: 305 scientists 43 D-Index: 336 scientists 44 D-Index: 330 scientists 45 D-Index: 348 scientists 46 D-Index: 291 scientists 47 D-Index: 275 scientists 48 D-Index: 272 scientists 49 D-Index: 273 scientists 50 D-Index: 263 scientists 51 D-Index: 232 scientists 52 D-Index: 266 scientists 53 D-Index: 217 scientists 54 D-Index: 199 scientists 55 D-Index: 177 scientists 56 D-Index: 202 scientists 57 D-Index: 204 scientists 58 D-Index: 166 scientists 59 D-Index: 177 scientists 60 D-Index: 166 scientists 61 D-Index: 152 scientists 62 D-Index: 143 scientists 63 D-Index: 150 scientists 64 D-Index: 124 scientists 65 D-Index: 119 scientists 66 D-Index: 120 scientists 67 D-Index: 118 scientists 68 D-Index: 82 scientists 69 D-Index: 98 scientists 70 D-Index: 94 scientists 71 D-Index: 105 scientists 72 D-Index: 74 scientists 73 D-Index: 84 scientists 74 D-Index: 70 scientists 75 D-Index: 67 scientists 76 D-Index: 78 scientists 77 D-Index: 60 scientists 78 D-Index: 59 scientists 79 D-Index: 52 scientists 80 D-Index: 47 scientists 81 D-Index: 38 scientists 82 D-Index: 48 scientists 83 D-Index: 42 scientists 84 D-Index: 42 scientists 85 D-Index: 43 scientists 86 D-Index: 29 scientists 87 D-Index: 37 scientists 88 D-Index: 29 scientists 89 D-Index: 30 scientists 90 D-Index: 34 scientists 91 D-Index: 20 scientists 92 D-Index: 22 scientists 93 D-Index: 17 scientists 94 D-Index: 19 scientists 95 D-Index: 24 scientists 96 D-Index: 21 scientists 97 D-Index: 20 scientists 98 D-Index: 24 scientists 99 D-Index: 17 scientists 100 D-Index: 17 scientists 101 D-Index: 21 scientists 102 D-Index: 25 scientists 103 D-Index: 18 scientists 104 D-Index: 26 scientists 105 D-Index: 19 scientists 106 D-Index: 15 scientists 107 D-Index: 10 scientists 108 D-Index: 13 scientists 109 D-Index: 15 scientists 110 D-Index: 12 scientists 111 D-Index: 8 scientists 112 D-Index: 7 scientists 113 D-Index: 9 scientists 114 D-Index: 6 scientists 115 D-Index: 12 scientists 116 D-Index: 7 scientists 117 D-Index: 8 scientists 118 D-Index: 3 scientists 119 D-Index: 5 scientists 120 D-Index: 7 scientists 121 D-Index: 2 scientists 122 D-Index: 4 scientists 123 D-Index: 8 scientists 124 D-Index: 7 scientists 125+ D-Index: 99 scientists
30 D-Index 125+

This scientist: 41 D-Index — 22nd percentile

22% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 125 D-Index or more.

Overview

William W. Hsieh is affiliated with the University of British Columbia in Canada and works primarily in the fields of Computer Science, Environmental Science, and Earth and Planetary Sciences. Their research extensively covers subfields including Artificial Intelligence, Atmospheric Science, Environmental Engineering, Global and Planetary Change, and Biomedical Engineering.

Their recent publications span several notable venues, with contributions to:

  • Bulletin of the American Meteorological Society
  • Environmental Data Science
  • Journal of Environmental Informatics
  • Plant Phenomics
  • arXiv (Cornell University)

Key topics addressed in their work include:

  • Meteorological Phenomena and Simulations
  • Hydrological Forecasting Using AI
  • Neural Networks and Applications
  • Machine Learning and ELM
  • Data Analysis with R
  • Climate variability and models
  • Optical Polarization and Ellipsometry

Their most recent papers consist of:

  • "The History and Practice of AI in the Environmental Sciences" (2021), published in Bulletin of the American Meteorological Society
  • "Evolution of machine learning in environmental science-A perspective" (2022), published in Environmental Data Science
  • "Improving Predictions by Nonlinear Regression Models from Outlying Input Data" (2023), published in Journal of Environmental Informatics
  • "Mitigating Illumination-, Leaf-, and View-Angle Dependencies in Hyperspectral Imaging Using Polarimetry" (2024), published in Plant Phenomics
  • "Improving predictions by nonlinear regression models from outlying input data" (2020), published in arXiv (Cornell University)

William W. Hsieh has collaborated frequently with several researchers including Sue Ellen Haupt, David John Gagne, Vladimir M. Krasnopolsky, Amy McGovern, and Caren Marzban.

Their book publication record includes a title published by Cambridge University Press:

  • "Introduction to Environmental Data Science" (2023)

Best Publications

  • Applying Neural Network Models to Prediction and Data Analysis in Meteorology and Oceanography

    William W. Hsieh;Benyang Tang

  • Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels

    William W. Hsieh

  • Daily streamflow forecasting by machine learning methods with weather and climate inputs

    Kabir Rasouli;William W. Hsieh;Alex J. Cannon

  • Crop yield forecasting on the Canadian Prairies by remotely sensed vegetation indices and machine learning methods

    Michael D. Johnson;William W. Hsieh;Alex J. Cannon;Andrew Davidson

  • Nonlinear principal component analysis by neural networks

    William W. Hsieh

  • Machine Learning Methods in the Environmental Sciences: Contents

    Unknown

  • Nonlinear multivariate and time series analysis by neural network methods

    William W. Hsieh

  • Nonlinear canonical correlation analysis by neural networks

    W. W. Hsieh

  • Forecasting ENSO Events: A Neural Network–Extended EOF Approach.

    Fredolin T. Tangang;Benyang Tang;Adam H. Monahan;William W. Hsieh

  • 2006 Special issue: Neural network forecasts of the tropical Pacific sea surface temperatures

    Aiming Wu;William W. Hsieh;Benyang Tang

  • Forecasting the equatorial Pacific sea surface temperatures by neural network models

    F. T. Tangang;W. W. Hsieh;B. Tang

  • The Free Kelvin Wave in Finite-Difference Numerical Models

    William W. Hsieh;Michael K. Davey;Roxana C. Wajsowicz

  • Forecasting daily streamflow using online sequential extreme learning machines

    Aranildo R. Lima;Alex J. Cannon;William W. Hsieh

  • Nonlinear Canonical Correlation Analysis of the Tropical Pacific Climate Variability Using a Neural Network Approach

    William W. Hsieh

  • Nonlinear regression in environmental sciences using extreme learning machines

    Aranildo R. Lima;Alex J. Cannon;William W. Hsieh

  • Skill Comparisons between Neural Networks and Canonical Correlation Analysis in Predicting the Equatorial Pacific Sea Surface Temperatures

    Benyang Tang;William W. Hsieh;Adam H. Monahan;Fredolin T. Tangang

  • Maize yield forecasting by linear regression and artificial neural networks in Jilin, China

    K. Matsumura;C. F. Gaitan;K. Sugimoto;A. J. Cannon

  • Interactive Feedback between the Tropical Pacific Decadal Oscillation and ENSO in a Coupled General Circulation Model

    Jung Choi;Soon Il An;Boris Dewitte;William W. Hsieh

  • Global climate change and ocean upwelling

    William W. Hsieh;George J. Boer

  • The Nonlinear Patterns of North American Winter Temperature and Precipitation Associated with ENSO

    Aiming Wu;William W. Hsieh;Amir Shabbar

  • Forecasting regional sea surface temperatures in the tropical Pacific by neural network models, with wind stress and sea level pressure as predictors

    Fredolin T. Tangang;William W. Hsieh;Benyang Tang

Frequent Co-Authors

Alex J. Cannon
Alex J. Cannon University of Victoria
Fredolin Tangang
Fredolin Tangang National University of Malaysia
Lawrence A. Mysak
Lawrence A. Mysak McGill University Health Centre
Soon-Il An
Soon-Il An Yonsei University
George J. Boer
George J. Boer Environment and Climate Change Canada
B.G. Ruessink
B.G. Ruessink Utrecht University
Kevin Hamilton
Kevin Hamilton University of Hawaii at Manoa
Francis W. Zwiers
Francis W. Zwiers University of Victoria
Richard E. Thomson
Richard E. Thomson Fisheries and Oceans Canada
Howard J. Freeland
Howard J. Freeland Fisheries and Oceans Canada

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