What is he best known for?
The fields of study he is best known for:
- Mathematical optimization
- Mechanical engineering
- Statistics
His primary areas of study are Mathematical optimization, Engineering design process, Genetic algorithm, Multi-objective optimization and Product design.
His Mathematical optimization study combines topics from a wide range of disciplines, such as Principle of maximum entropy, Artificial intelligence and Probability distribution.
He combines subjects such as Design of experiments, Algorithm, Baseline and Robustness with his study of Engineering design process.
Shapour Azarm works mostly in the field of Genetic algorithm, limiting it down to topics relating to Pareto principle and, in certain cases, Function and Truss.
Multi-objective optimization is closely attributed to Robust optimization in his study.
His work is dedicated to discovering how Product design, New product development are connected with Operations research and other disciplines.
His most cited work include:
- Metrics for Quality Assessment of a Multiobjective Design Optimization Solution Set (206 citations)
- Product Design Selection Under Uncertainty and With Competitive Advantage (162 citations)
- Multi-objective robust optimization using a sensitivity region concept (152 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Mathematical optimization, Engineering design process, Multi-objective optimization, Optimization problem and Genetic algorithm.
Shapour Azarm frequently studies issues relating to Algorithm and Mathematical optimization.
His Engineering design process research integrates issues from Product design, Kriging and Robustness.
His research investigates the link between Multi-objective optimization and topics such as Control theory that cross with problems in Reduction and Leg mechanism.
His work carried out in the field of Optimization problem brings together such families of science as Linear system and Constraint.
The concepts of his Genetic algorithm study are interwoven with issues in Evolutionary algorithm, Baseline and Truss.
He most often published in these fields:
- Mathematical optimization (49.73%)
- Engineering design process (22.40%)
- Multi-objective optimization (18.58%)
What were the highlights of his more recent work (between 2016-2021)?
- Control theory (12.02%)
- Mathematical optimization (49.73%)
- Dynamic data (2.19%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Control theory, Mathematical optimization, Dynamic data, Probability distribution and Linear system.
His Robustness study in the realm of Control theory interacts with subjects such as Vehicle routing problem and Underwater.
His Mathematical optimization study is mostly concerned with Robust optimization, Genetic algorithm, Discrete optimization, Continuous optimization and Multi-swarm optimization.
His work deals with themes such as Reduction and Regular polygon, which intersect with Robust optimization.
In his work, State is strongly intertwined with Task, which is a subfield of Genetic algorithm.
His biological study spans a wide range of topics, including Optimization problem, Controllability and Semidefinite programming.
Between 2016 and 2021, his most popular works were:
- Optimal actuator placement for linear systems with limited number of actuators (20 citations)
- Fast Multipole Method for Nonlinear, Unsteady Aerodynamic Simulations (6 citations)
- Estimating damage size and remaining useful life in degraded structures using deep learning-based multi-source data fusion: (5 citations)
In his most recent research, the most cited papers focused on:
- Mechanical engineering
- Statistics
- Artificial intelligence
Shapour Azarm spends much of his time researching Fast multipole method, Aerodynamics, Aeroelasticity, Dynamic data and Control theory.
His Fast multipole method research incorporates a variety of disciplines, including Nonlinear system, Mechanics, Computational physics, Vortex lattice method and Computation.
His research in Aeroelasticity intersects with topics in Control engineering, Flight envelope, Decision support system and Co-simulation.
The concepts of his Control theory study are interwoven with issues in Systems design and Greedy algorithm.
His Systems design study combines topics in areas such as Linear system and Mathematical optimization.
His primary area of study in Mathematical optimization is in the field of Semidefinite programming.
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