World's Best Scientists 2026 revealed!
Roy E. Welsch

Roy E. Welsch

D-Index & Metrics

Engineering and Technology

D-Index
33
Citations
22580
World Ranking
9307
National Ranking
2601

Roy E. Welsch 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 Roy E. Welsch 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: 116 publications — 14th percentile

14% of scientists in this discipline score the same or lower.

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

Roy E. Welsch 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 Roy E. Welsch 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: 33 D-Index — 5th percentile

5% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 1987 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 1981 - Fellow of the American Statistical Association (ASA)

Overview

Roy E. Welsch is affiliated with MIT in the United States and works primarily in the field of Computer Science, with a focus on areas such as Artificial Intelligence, Statistics and Probability, Computer Networks and Communications, Computer Vision and Pattern Recognition, and Endocrinology, Diabetes and Metabolism.

The scientist's recent published papers cover a range of topics and include:

  • "Causal inference in medical records and complementary systems pharmacology for metformin drug repurposing towards dementia" (2022), published in Nature Communications
  • "Self-training method based on GCN for semi-supervised short text classification" (2022), published in Information Sciences
  • "Dual Autoencoders Generative Adversarial Network for Imbalanced Classification Problem" (2020), published in IEEE Access
  • "Predicting video engagement using heterogeneous DeepWalk" (2021), published in Neurocomputing
  • "Ambivert degree identifies crucial brain functional hubs and improves detection of Alzheimer's Disease and Autism Spectrum Disorder" (2020), published in NeuroImage Clinical

Frequent collaborators include:

  • Stan N. Finkelstein
  • Erik Cambria
  • Kenney Ng
  • Jagath C. Rajapakse
  • Lisa Tucker-Kellogg

Roy E. Welsch has contributed to several publication venues multiple times. The most frequent are:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Neurocomputing
  • Cognitive Computation
  • bioRxiv (Cold Spring Harbor Laboratory)

The scientist's primary research topics include:

  • Advanced Causal Inference Techniques
  • Pressure Ulcer Prevention and Management
  • Stock Market Forecasting Methods
  • Statistical Methods and Inference
  • Diabetic Foot Ulcer Assessment and Management
  • Advanced Text Analysis Techniques
  • Health Systems, Economic Evaluations, Quality of Life

Throughout their career, Roy E. Welsch has been recognized as a Fellow by two major organizations: the American Association for the Advancement of Science (AAAS) in 1987 and the American Statistical Association (ASA) in 1981.

Best Publications

  • Regression Diagnostics: Identifying Influential Data and Sources of Collinearity

    David A. Belsley;Edwin Kuh;Roy E. Welsch

  • The Hat Matrix in Regression and ANOVA

    David C. Hoaglin;Roy E. Welsch

  • Algorithm 573: NL2SOL—An Adaptive Nonlinear Least-Squares Algorithm [E4]

    John E. Dennis;Roy E. Welsch

  • Efficient Bounded-Influence Regression Estimation

    William S. Krasker;Roy E. Welsch

  • Efficient Computing of Regression Diagnostics

    Paul F. Velleman;Roy E. Welsch

  • Natural language based financial forecasting: a survey

    Frank Z. Xing;Erik Cambria;Roy E. Welsch

  • Descriptors of Oxygen-Evolution Activity for Oxides: A Statistical Evaluation

    Wesley Terrence Hong;Roy E Welsch;Yang Shao-Horn

  • Stepwise Multiple Comparison Procedures

    Roy E. Welsch

  • Distinguishing between facts and opinions for sentiment analysis: survey and challenges

    Iti Chaturvedi;Erik Cambria;Roy E. Welsch;Francisco Herrera

  • Anomaly detection via a Gaussian Mixture Model for flight operation and safety monitoring

    Lishuai Li;R. John Hansman;Rafael Palacios;Roy Welsch

  • Techniques for nonlinear least squares and robust regression

    John E. Dennis;Roy E. Welsch

  • Linear regression diagnostics

    Roy E. Welsch;Edwin Kuh

  • Logistics agglomeration in the US

    Liliana Rivera;Yossi Sheffi;Roy Welsch

  • Regression Sensitivity Analysis and Bounded-Influence Estimation

    Roy E. Welsch

  • Algorithm 717: Subroutines for maximum likelihood and quasi-likelihood estimation of parameters in nonlinear regression models

    David S. Bunch;Roy E. Welsch

  • Intelligent Asset Allocation via Market Sentiment Views

    Frank Z. Xing;Erik Cambria;Roy E. Welsch

  • Detecting and Assessing Collinearity

    David A. Belsley;Edwin Kuh;Roy E. Welsch

  • INFLUENCE FUNCTIONS AND REGRESSION DIAGNOSTICS

    Roy E. Welsch

  • Deep learning enables automated scoring of liver fibrosis stages

    Yang Yu;Jiahao Wang;Chan Way Ng;Yukun Ma

  • Learning word dependencies in text by means of a deep recurrent belief network

    Iti Chaturvedi;Yew-Soon Ong;Ivor W. Tsang;Roy E. Welsch

Frequent Co-Authors

Jagath C. Rajapakse
Jagath C. Rajapakse Nanyang Technological University
Erik Cambria
Erik Cambria Nanyang Technological University
Paul Matsudaira
Paul Matsudaira National University of Singapore
Hanry Yu
Hanry Yu National University of Singapore
John E. Dennis
John E. Dennis Rice University
Vincent T. K. Chow
Vincent T. K. Chow National University of Singapore
Patrick Tan
Patrick Tan Duke NUS Graduate Medical School
Jie Yan
Jie Yan National University of Singapore
Sanford Weisberg
Sanford Weisberg University of Minnesota

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