World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
32
Citations
7365
World Ranking
9507
National Ranking
598

Alexander Gammerman 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 Alexander Gammerman 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: 155 publications — 29th percentile

29% of scientists in this discipline score the same or lower.

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

Alexander Gammerman 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 Alexander Gammerman 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: 32 D-Index — 3rd percentile

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

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

Overview

Alexander Gammerman is affiliated with Royal Holloway University of London in the United Kingdom. Their research primarily falls within the field of Computer Science, with a focus on subfields like Artificial Intelligence, Statistics and Probability, General Health Professions, Statistics, Probability and Uncertainty, and Signal Processing.

The main topics in Gammerman's body of work include Statistical Methods and Inference, Data Stream Mining Techniques, Neural Networks and Applications, Gaussian Processes and Bayesian Inference, Time Series Analysis and Forecasting, Bayesian Modeling and Causal Inference, and Bayesian Methods and Mixture Models.

Frequent publication venues for Gammerman's work include arXiv (Cornell University) and Pattern Recognition. Some of their recent papers are:

  • Retrain or not retrain: Conformal test martingales for change-point detection (2021), arXiv (Cornell University)
  • Special Issue on Conformal and Probabilistic Prediction with Applications: Preface (2022), Pattern Recognition
  • Conformal testing: binary case with Markov alternatives (2021), arXiv (Cornell University)
  • Protected probabilistic classification (2021), arXiv (Cornell University)
  • Calibrated Large Language Models for Binary Question Answering (2024), arXiv (Cornell University)

Gammerman's frequent co-authors include Vladimir Vovk, Ilia Nouretdinov, Ivan Petej, Marco Cristani, and Matteo Fontana.

Best Publications

  • Algorithmic Learning in a Random World

    Vladimir Vovk;Alex Gammerman;Glenn Shafer

  • Ridge Regression Learning Algorithm in Dual Variables

    Craig Saunders;Alexander Gammerman;Volodya Vovk

  • Learning by transduction

    A. Gammerman;V. Vovk;V. Vapnik

  • Inductive Confidence Machines for Regression

    Harris Papadopoulos;Kostas Proedrou;Volodya Vovk;Alexander Gammerman

  • Algorithmic Learning in a Random World

    Unknown

  • Machine-Learning Applications of Algorithmic Randomness

    Volodya Vovk;Alexander Gammerman;Craig Saunders

  • Transductive Confidence Machines for Pattern Recognition.

    Kostas Proedrou;Ilia Nouretdinov;Volodya Vovk;Alexander Gammerman

  • Transduction with Confidence and Credibility

    Craig Saunders;Alexander Gammerman;Volodya Vovk

  • Transductive confidence machines for pattern recognition

    Kostas Proedrou;Ilia Nouretdinov;Volodya Vovk;Alexander Gammerman

  • Machine learning classification with confidence: application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression.

    Ilia Nouretdinov;Sergi G. Costafreda;Alexander Gammerman;Alexey Ya. Chervonenkis

  • Hedging Predictions in Machine Learning

    Alexander Gammerman;Vladimir Vovk

  • Sequence alignment kernel for recognition of promoter regions.

    Leo Gordon;Alexey Ya. Chervonenkis;Alex J. Gammerman;Ilham A. Shahmuradov

  • Support vector regression with ANOVA decomposition kernels

    Mark O. Stitson;Alex Gammerman;Vladimir Vapnik;Volodya Vovk

  • Regression conformal prediction with nearest neighbours

    Harris Papadopoulos;Vladimir Vovk;Alex Gammerman

  • Support vector density estimation

    Jason Weston;Alex Gammerman;Mark O. Stitson;Vladimir Vapnik

  • Machine-learning algorithms for credit-card applications

    R. H. Davis;D. B. Edelman;A. J. Gammerman

  • Prediction algorithms and confidence measures based on algorithmic randomness theory

    Alex Gammerman;Volodya Vovk

  • On-line predictive linear regression

    Vladimir Vovk;Ilia Nouretdinov;Alex Gammerman

  • Probabilistic reasoning in evidential assessment

    C.G.G. Aitken;A.J. Gammerman

  • Criteria of Efficiency for Conformal Prediction

    Vladimir Vovk;Valentina Fedorova;Ilia Nouretdinov;Alexander Gammerman

  • Reliable Confidence Measures for Medical Diagnosis With Evolutionary Algorithms

    A Lambrou;H Papadopoulos;A Gammerman

  • Testing exchangeability on-line

    Vladimir Vovk;Ilia Nouretdinov;Alex Gammerman

  • Criteria of efficiency for conformal prediction

    Vladimir Vovk;Ilia Nouretdinov;Valentina Fedorova;Ivan Petej

Frequent Co-Authors

Usha Menon
Usha Menon University College London
Ian Jacobs
Ian Jacobs University of New South Wales
Rainer Cramer
Rainer Cramer University of Reading
Mike Waterfield
Mike Waterfield Ludwig Cancer Research
Vladimir Vapnik
Vladimir Vapnik Princeton University
Jaakko Astola
Jaakko Astola Tampere University
Andrew N. Nicolaides
Andrew N. Nicolaides Imperial College London
Victor V. Solovyev
Victor V. Solovyev Royal Holloway University of London
Constantinos S. Pattichis
Constantinos S. Pattichis University of Cyprus
Ola Blixt
Ola Blixt University of Copenhagen

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