2026 Andy J. Keane: Engineering and Technology Researcher – H-Index, Publications & Awards

D-Index & Metrics

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Engineering and Technology	53	3303	3163	215	200	364	20209

Discipline name

D-Index

World Ranking

Current World Ranking

National Ranking

Current National Ranking

Publications

Citations

Engineering and Technology

3303

3163

215

200

364

20209

Engineering and Technology

D-Index

Citations

20209

World Ranking

3303

National Ranking

215

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

3125
Citations
Recent advances in surrogate-based optimization

Alexander I.J. Forrester;Andy J. Keane

2623
Citations
Engineering Design via Surrogate Modelling

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

2426
Citations
Multi-fidelity optimization via surrogate modelling

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

1160
Citations
Meta-Lamarckian learning in memetic algorithms

Yew Soon Ong;A.J. Keane

805
Citations
Evolutionary Optimization of Computationally Expensive Problems via Surrogate Modeling

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

673
Citations
Combining Global and Local Surrogate Models to Accelerate Evolutionary Optimization

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

481
Citations
Statistical Improvement Criteria for Use in Multiobjective Design Optimization

Andy J. Keane

397
Citations
Computational Approaches for Aerospace Design: The Pursuit of Excellence

Andy J. Keane;Prasanth B. Nair

370
Citations
On the Design of Optimization Strategies Based on Global Response Surface Approximation Models

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

340
Citations
Design and analysis of 'noisy' computer experiments

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

293
Citations
Optimization using surrogate models and partially converged computational fluid dynamics simulations

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

239
Citations
Infill sampling criteria for surrogate-based optimization with constraint handling

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

213
Citations
Wing Optimization Using Design of Experiment, Response Surface, and Data Fusion Methods

A. J. Keane

212
Citations
Kriging Hyperparameter Tuning Strategies

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

205
Citations
Multi-Objective Optimization Using Surrogates

Ivan Voutchkov;Andy Keane

197
Citations
Surrogate-Assisted Evolutionary Optimization Frameworks for High-Fidelity Engineering Design Problems

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

189
Citations
Metamodeling techniques for evolutionary optimization of computationally expensive problems: promises and limitations

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

175
Citations
Stochastic Reduced Basis Methods

Prasanth B. Nair;Andrew J. Keane

161
Citations
Optimal orthogonal-array-based latin hypercubes

Stephen Leary;Atul Bhaskar;Andy Keane

145
Citations
A Knowledge-Based Approach To Response Surface Modelling in Multifidelity Optimization

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

140
Citations