Ph.D. student, University of Patras, Department of Mechanical Engineering and Aeronautics.
Research Interest: Machine Learning, Reduced Order Modeling, Digital twins, Partial Differential Equations, Numerical Simulations, Uncertainty Quantification
His current research interest includes the employment of non-intrusive reduced order modeling methods for guided wave propagation in the field of computational structural dynamics. The main target is to estimate the uncertainty quantification of the variations in the material properties. Previously he has worked in the implementation of ROM in the field of computational fluid dynamics for bioengineering applications.
Mr. George Drakoulas is a mechanical and aeronautical engineer motivated by innovative concepts with practical applications. Currently, conducting Ph.D. research for Reduced-Order Models (ROMs) based on non-intrusive Machine Learning methods, aiming to implement the technology of real-time Digital Twins and solve industrial problems. He has four years of industrial experience at FEAC Engineering as a simulation software engineer, with a broad participation in computational mechanics projects, in the field of aerospace, biomechanics, marine, and materials. Specialized in Computational Structural Mechanics with excellent knowledge of Computational Fluid Dynamics. His current work addresses the implementation of ROMs to solve the uncertainty quantification and assist structural health monitoring systems. Highly interested also in novel technics to combine Multiobjective Optimization Algorithms & Deep Learning with physics-based simulations, to predict and improve operational performance.