معرفی
Professor Nikolaos Dervilis is a faculty member in the Department of Mechanical Engineering at the University of Sheffield, serving as Director of Research and Innovation for the School of Mechanical, Aerospace and Civil Engineering. He holds a BSc from the National and Kapodistrian University of Athens, an MSc in Sustainable and Renewable Energy Systems from the University of Edinburgh, and a PhD from the University of Sheffield in Mechanical Engineering with a focus on machine learning for Structural Health Monitoring (SHM). His research emphasizes SHM, renewable energy systems (particularly wind turbines), data analysis, nonlinear dynamics, and advanced signal processing.
His work spans population-based SHM (PBSHM), machine learning applications in structural dynamics, and probabilistic modeling. Recent publications focus on active learning frameworks, Bayesian methods, and generative models for damage prognosis. He collaborates with industry on wind energy and has contributed to datasets for experimental bridges and aerospace components. Notably, he leads efforts in transfer learning and domain adaptation for heterogeneous structural populations.
Research highlights include developing frameworks for risk-informed decision support, model selection via approximate Bayesian computation, and digital twin tools for engineering systems. His lab, part of the Dynamics Research Group, addresses challenges in energy systems, composite materials, and condition monitoring of critical infrastructure.
