What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Mechanical engineering
- Statistics
Mathematical optimization, Engineering design process, Algorithm, Surrogate model and Kriging are his primary areas of study.
Many of his research projects under Mathematical optimization are closely connected to Gaussian process with Gaussian process, tying the diverse disciplines of science together.
Andy J. Keane has included themes like Scheme and Function, Systems engineering in his Engineering design process study.
His Algorithm study combines topics in areas such as High fidelity, Optimal design, Robustness and Maxima and minima.
His study looks at the relationship between Surrogate model and topics such as Benchmark, which overlap with Adaptive learning, Adaptive system and Nonlinear programming.
His research in Kriging intersects with topics in Design of experiments, Sample, Noise and Extension.
His most cited work include:
- Recent advances in surrogate-based optimization (1329 citations)
- Engineering Design via Surrogate Modelling: A Practical Guide (1199 citations)
- Engineering Design via Surrogate Modelling (1031 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Mathematical optimization, Engineering design process, Finite element method, Kriging and Genetic algorithm.
His research integrates issues of Algorithm and Optimal design in his study of Mathematical optimization.
His study looks at the relationship between Engineering design process and fields such as Systems engineering, as well as how they intersect with chemical problems.
His Finite element method research is multidisciplinary, relying on both Vibration, Numerical analysis, Mathematical analysis and Mechanical engineering.
The study of Kriging is intertwined with the study of Computational fluid dynamics in a number of ways.
His Genetic algorithm study incorporates themes from Design of experiments and Artificial intelligence.
He most often published in these fields:
- Mathematical optimization (27.11%)
- Engineering design process (12.24%)
- Finite element method (10.20%)
What were the highlights of his more recent work (between 2012-2021)?
- Mathematical optimization (27.11%)
- Kriging (9.62%)
- Mechanical engineering (8.45%)
In recent papers he was focusing on the following fields of study:
His main research concerns Mathematical optimization, Kriging, Mechanical engineering, Combustor and Engineering design process.
Mathematical optimization is closely attributed to Function in his work.
His biological study spans a wide range of topics, including Minimum weight, Polygon mesh, Optimal design and Topology.
His research in Mechanical engineering tackles topics such as Finite element method which are related to areas like Surrogate model, Gas compressor, Set and Aileron.
His Combustor research is multidisciplinary, relying on both Computational fluid dynamics and Combustion chamber.
The concepts of his Engineering design process study are interwoven with issues in Process flowsheeting, Design process, Iterative design and Engineering management.
Between 2012 and 2021, his most popular works were:
- An integrated conceptual design study using span morphing technology (27 citations)
- Multifidelity Multidisciplinary Whole-Engine Thermomechanical Design Optimization (19 citations)
- Performance of an ensemble of ordinary, universal, non-stationary and limit Kriging predictors (13 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Mechanical engineering
- Statistics
Andy J. Keane spends much of his time researching Mathematical optimization, Mechanical engineering, Surrogate model, Engineering design process and Kriging.
His research in Mathematical optimization is mostly concerned with Robust design optimization.
His work carried out in the field of Mechanical engineering brings together such families of science as Face and Finite element method.
His Surrogate model study combines topics from a wide range of disciplines, such as Analytic function, Selection and Limit.
His studies in Engineering design process integrate themes in fields like Operations research, Iterative and incremental development, Search engine and Aerospace.
Andy J. Keane has researched Kriging in several fields, including Minimum weight, Fuselage, Optimal design and Multi-objective optimization.
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