World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
53
Citations
20209
World Ranking
3305
National Ranking
214

Andy J. Keane 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 Andy J. Keane 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: 364 publications — 85th percentile

85% of scientists in this discipline score the same or lower.

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

Andy J. Keane 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 Andy J. Keane 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: 53 D-Index — 66th percentile

66% of scientists in this discipline score the same or lower.

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

Overview

Andy J. Keane is a researcher affiliated with the University of Southampton in the United Kingdom. Their work primarily focuses on fields within engineering, particularly computational mechanics and optimization methods.

Their recent publications cover a range of topics related to optimization and computational design. Notable papers include:

  • Robust design optimization using surrogate models (2020), Journal of Computational Design and Engineering
  • The Potential of a Multifidelity Approach to Gas Turbine Combustor Design Optimization (2020), Journal of Engineering for Gas Turbines and Power
  • Development of an adaptive infill criterion for constrained multi-objective asynchronous surrogate-based optimization (2020), Journal of Global Optimization
  • Extending Point-Based Deep Learning Approaches for Better Semantic Segmentation in CAD (2023), Computer-Aided Design
  • Multiresolution surface blending for detail reconstruction (2022), Graphics and Visual Computing

The main fields of study reflected in their work include:

  • Engineering

Within engineering, they have contributed to the following subfields:

  • Computational Mechanics
  • Statistics, Probability and Uncertainty
  • Computational Theory and Mathematics
  • Management Science and Operations Research
  • Aerospace Engineering

Keane's research engages with several core topics:

  • Probabilistic and Robust Engineering Design
  • 3D Shape Modeling and Analysis
  • Advanced Multi-Objective Optimization Algorithms
  • Optimal Experimental Design Methods
  • Advanced Numerical Analysis Techniques
  • Manufacturing Process and Optimization
  • Computer Graphics and Visualization Techniques

The researcher has frequently published in the following venues:

  • arXiv (Cornell University)
  • Journal of Engineering for Gas Turbines and Power
  • The Surgeon
  • Journal of Computational Design and Engineering
  • Journal of Global Optimization

Among the frequent collaborators in Andy J. Keane's research are:

  • David J. J. Toal
  • Ivan Voutchkov
  • Marco Nuñez
  • Xu Zhang
  • Gerico Vidanes

Best Publications

  • Engineering Design via Surrogate Modelling: A Practical Guide

    Alexander I. J Forrester;András Sóbester;A. J. Keane

  • Recent advances in surrogate-based optimization

    Alexander I.J. Forrester;Andy J. Keane

  • Engineering Design via Surrogate Modelling

    Alexander I. J. Forrester;Andrs Sbester;Andy J. Keane

  • Multi-fidelity optimization via surrogate modelling

    Alexander I.J Forrester;András Sóbester;Andy J Keane

  • Meta-Lamarckian learning in memetic algorithms

    Yew Soon Ong;A.J. Keane

  • Evolutionary Optimization of Computationally Expensive Problems via Surrogate Modeling

    Yew S. Ong;Prasanth B. Nair;Andrew J. Keane

  • Combining Global and Local Surrogate Models to Accelerate Evolutionary Optimization

    Zongzhao Zhou;Yew Soon Ong;P.B. Nair;A.J. Keane

  • Statistical Improvement Criteria for Use in Multiobjective Design Optimization

    Andy J. Keane

  • Computational Approaches for Aerospace Design: The Pursuit of Excellence

    Andy J. Keane;Prasanth B. Nair

  • On the Design of Optimization Strategies Based on Global Response Surface Approximation Models

    András Sóbester;Stephen J. Leary;Andy J. Keane

  • Design and analysis of 'noisy' computer experiments

    Alexander I. J. Forrester;Andy J. Keane;Neil W. Bressloff

  • Optimization using surrogate models and partially converged computational fluid dynamics simulations

    Alexander I.J Forrester;Neil W Bressloff;Andy J Keane

  • Infill sampling criteria for surrogate-based optimization with constraint handling

    James Parr;A.J. Keane;A.I.J. Forrester;C.M.E. Holden

  • Wing Optimization Using Design of Experiment, Response Surface, and Data Fusion Methods

    A. J. Keane

  • Kriging Hyperparameter Tuning Strategies

    David J.J. Toal;Neil W. Bressloff;Andy J. Keane

  • Multi-Objective Optimization Using Surrogates

    Ivan Voutchkov;Andy Keane

  • Surrogate-Assisted Evolutionary Optimization Frameworks for High-Fidelity Engineering Design Problems

    Yew Soon Ong;P. B. Nair;A. J. Keane;K. W. Wong

  • Metamodeling techniques for evolutionary optimization of computationally expensive problems: promises and limitations

    Mohammed A. El-Beltagy;Prasanth B. Nair;Andy J. Keane

  • Stochastic Reduced Basis Methods

    Prasanth B. Nair;Andrew J. Keane

  • Optimal orthogonal-array-based latin hypercubes

    Stephen Leary;Atul Bhaskar;Andy Keane

  • A Knowledge-Based Approach To Response Surface Modelling in Multifidelity Optimization

    Stephen J. Leary;Atul Bhaskar;Andy J. Keane

Frequent Co-Authors

Yew-Soon Ong
Yew-Soon Ong Nanyang Technological University
Michael J. Brennan
Michael J. Brennan Sao Paulo State University
Stephen J. Elliott
Stephen J. Elliott University of Southampton
Wendy Hall
Wendy Hall University of Southampton
Robin S. Langley
Robin S. Langley University of Cambridge
Eric Rogers
Eric Rogers University of Southampton
Nigel Shadbolt
Nigel Shadbolt University of Oxford
Carole Goble
Carole Goble University of Manchester
R.J. Astley
R.J. Astley University of Southampton
R. Eatock Taylor
R. Eatock Taylor University of Oxford

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