Summary
Charilaos Mylonas is a Senior Consultant based in Zurich with a decade of experience at the intersection of scientific computing, scalable simulations and data science. He holds advanced degrees from ETH Zürich and a background in structural engineering, and his PhD work focused on large-scale wind farm simulations and probabilistic monitoring using generative deep models. He combines strong numerical methods and software engineering—tensor decompositions, polynomial chaos, distributed simulation—with modern deep learning expertise in transformers, computer vision and graph neural networks. At Deloitte he translates research-grade probabilistic ML into production-relevant solutions, leveraging prior contributions to uncertainty quantification tooling and high-performance code. Known for bridging theory and practice, he often applies stochastic variational Bayes and scalable architectures to tackle real-world predictive and monitoring challenges.
10 years of coding experience
6 years of employment as a software developer
Dipl. Ing. Civil Engineering, Structural Analysis, 7.76/10 (Very Good), Dipl. Ing. Civil Engineering, Structural Analysis, 7.76/10 (Very Good) at Aristoteleion Panepistimion Thessalonikis
Master’s Degree, Computational Science and Engineering, 5.06/6.00, Master’s Degree, Computational Science and Engineering, 5.06/6.00 at Eidgenössische Technische Hochschule Zürich