What is he best known for?
The fields of study he is best known for:
- Operating system
- Artificial intelligence
- Algorithm
His scientific interests lie mostly in Mathematical optimization, Genetic algorithm, Algorithm, Mechanics and Nanofluid.
In the subject of general Mathematical optimization, his work in Optimization problem, Optimization algorithm and Tabu search is often linked to Shortest path problem, thereby combining diverse domains of study.
His work deals with themes such as Particle swarm optimization, Very-large-scale integration, Heuristics and Heuristic, which intersect with Genetic algorithm.
He specializes in Algorithm, namely Simulated annealing.
His Heat transfer study in the realm of Mechanics connects with subjects such as Magnetohydrodynamics.
He studied Heuristic and Combinatorial optimization that intersect with Metaheuristic.
His most cited work include:
- Iterative Computer Algorithms with Applications in Engineering: Solving Combinatorial Optimization Problems (238 citations)
- VLSI Physical Design Automation: Theory and Practice (235 citations)
- Evolutionary algorithms, simulated annealing and tabu search: a comparative study (161 citations)
What are the main themes of his work throughout his whole career to date?
Sadiq M. Sait focuses on Mathematical optimization, Algorithm, Very-large-scale integration, Genetic algorithm and Tabu search.
As part of the same scientific family, Sadiq M. Sait usually focuses on Mathematical optimization, concentrating on Fuzzy logic and intersecting with Domain.
His research in Algorithm intersects with topics in Evolutionary algorithm, Multi-objective optimization and Electronic circuit.
The Very-large-scale integration study which covers Standard cell that intersects with Integrated circuit layout.
He combines subjects such as Integrated circuit design and Iterative method with his study of Genetic algorithm.
His work carried out in the field of Tabu search brings together such families of science as Network topology, CMOS and Search algorithm.
He most often published in these fields:
- Mathematical optimization (27.24%)
- Algorithm (23.45%)
- Very-large-scale integration (17.24%)
What were the highlights of his more recent work (between 2017-2021)?
- Mechanics (7.24%)
- Mathematical optimization (27.24%)
- Nanofluid (4.48%)
In recent papers he was focusing on the following fields of study:
Sadiq M. Sait mainly investigates Mechanics, Mathematical optimization, Nanofluid, Materials science and Optimization algorithm.
His work on Heat transfer, Flow and Flow as part of general Mechanics study is frequently connected to Thermal radiation, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Metaheuristic study, which is part of a larger body of work in Mathematical optimization, is frequently linked to Machining, bridging the gap between disciplines.
His Metaheuristic study integrates concerns from other disciplines, such as Evolutionary algorithm, Optimization problem and Differential evolution.
His Nanofluid study combines topics from a wide range of disciplines, such as Computer simulation and Nonlinear system.
Sadiq M. Sait works mostly in the field of Optimization algorithm, limiting it down to concerns involving Algorithm and, occasionally, Benchmark.
Between 2017 and 2021, his most popular works were:
- FPGA-Based Accelerators of Deep Learning Networks for Learning and Classification: A Review (86 citations)
- Numerical Simulation and Mathematical Modeling of Electro-Osmotic Couette–Poiseuille Flow of MHD Power-Law Nanofluid with Entropy Generation (79 citations)
- A hybrid investigation on numerical and analytical solutions of electro-magnetohydrodynamics flow of nanofluid through porous media with entropy generation (61 citations)
In his most recent research, the most cited papers focused on:
- Operating system
- Artificial intelligence
- Computer network
His primary scientific interests are in Mechanics, Optimization algorithm, Nanofluid, Materials science and Mathematical optimization.
His Mechanics research is multidisciplinary, incorporating perspectives in Partial differential equation and Porous medium.
His work deals with themes such as Shape optimization, Automotive engineering, Brake and Metamodeling, which intersect with Optimization algorithm.
His Metamodeling research integrates issues from Simulated annealing and Algorithm.
He has researched Nanofluid in several fields, including Computer simulation and Nonlinear system.
His work on Nelder–Mead method and Metaheuristic as part of general Mathematical optimization study is frequently linked to Machining, bridging the gap between disciplines.
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