Phaedon-Stelios Koutsourelakis

Prof. Phaedon-Stelios Koutsourelakis is a Professor of Continuum Mechanics at the Technical University of Munich (TUM), affiliated with the TUM School of Engineering and Design. His research focuses on computational strategies for modeling and analyzing physical systems with a strong emphasis on uncertainty quantification, multiscale phenomena, and stochastic systems. He holds a PhD from Princeton University and has held academic positions at institutions including Cornell University, Heriot-Watt University, and the Lawrence Livermore National Laboratory.

His educational background includes a degree from the National Technical University of Athens and a PhD from Princeton University (1998). Key research areas include data-driven coarse-graining techniques, Bayesian inference in engineering systems, and physics-aware machine learning models for high-dimensional problems. He has received notable awards such as the Top Teaching Trophy from the Munich School of Engineering (2014–2016) and the Dean’s First Year Merit Prize at Princeton (1998).

His work bridges computational mechanics with statistical methods, addressing challenges in materials design, structural health monitoring, and predictive modeling under uncertainty. Recent projects include developing physics-constrained deep learning frameworks for surrogate modeling and quantifying model bias in digital twins of infrastructure systems.

Notable contributions include the Predictive Coarse-Graining framework and probabilistic methods for uncertainty quantification in heterogeneous media. His research also extends to optimization under uncertainty and interdisciplinary applications in biomedical engineering and materials science.