Dimitrios Dimogiannopoulos

Dimitrios Dimogiannopoulos is a Professor at the Department of Design and Production Engineering, School of Engineering, University of West Attica since 2010. His expertise focuses on Automatic Control Systems with specialization in Modeling, Simulation and Applications in Algorithmic Diagnosis of System Failures within Industrial Production Systems.

His research interests span across multiple domains of control systems and non-destructive testing. He specializes in Stochastic system identification and (non-)linear control, Adaptive control of systems, and the Development of non-contact/contact-free sensors for non-destructive algorithmic detection and diagnosis. His work has significant applications in aeronautics, biomedicine, food technology, and polymer composites, demonstrating the interdisciplinary nature of his research.

His recent publications reveal a clear research trajectory focusing on magnetoelastic sensor technologies, structural health monitoring, and non-destructive testing methodologies. The articles demonstrate consistent advancement in contact-less sensing techniques, particularly for composite materials and food quality assessment applications. His work combines theoretical control systems approaches with practical engineering solutions for real-world problems in structural integrity monitoring and quality control.

His scientific achievements include:

• National Patent on non-destructive methodology for evaluating mechanical properties of catches

Professor Dimogiannopoulos teaches undergraduate courses including Automated Control Systems I & II and Non-Destructive Testing. At the postgraduate level, he instructs Analysis of Technologically Advanced Applications for the M.A. in Production and Service Automation, and Advanced Control Topics and Surveillance Systems for the M.A. in New Technologies in Shipping & Transportation. He leads the Non-Destructive Testing and Systems Diagnosis Methodologies research laboratory, where his team develops innovative approaches to system health monitoring and fault diagnosis.