I hold a Ph.D. and M.Sc. from ETH Zurich and specialize in Machine Learning, with focus in deep learning, scientific computing, software engineering, and I have worked on consulting projects in risk management for financial institutions.
🎓During my Ph.D., I focused on developing cutting-edge deep learning techniques, including Graph Neural Networks, Bayesian Deep Learning for Generative Modeling (e.g., VAEs for graph-structured data), and Bayesian predictive models for time-series on graphs. I also contributed to Structural Health Monitoring (SHM) research, designing Bayesian models for high-frequency time-series and co-authoring work on Neural ODEs in Engineering.
đź’Ľ In my Big4 consulting career, I worked on energy market analytics, liquidity and credit risk automation systems, and developed cryptocurrency transaction analytics prototypes. I played a key role in early asset development for Retrieval-Augmented Generation (RAG) LLM prototypes, introduced DevOps processes, and conducted internal seminars on RAG and LLM technologies.
🎹 Outside of work, I enjoy playing music, tinkering with microcontrollers and software automation, and staying engaged with deep learning research. See below for some of my recent personal projects.
PhD Machine Learning for SHM under Uncertainty, 2021
ETH Zurich
MSc Computational Science & Engineering, 2015
ETH Zurich
MSc in Civil Engineering, 2012
Aristotle University of Thessaloniki
Chair of Structural Mechanics and Monitoring. Research topics: