Researcher in Operations Research & Scientific Machine Learning
Specializing in stochastic optimization, complex systems modeling, and data-driven decision-making. Applying advanced analytics to production systems, biomedical data, and supply chain management.
PhD, University of Geneva · Postgraduate, EPFL · Former CERN Associate.
PhD in Economics and Management from the University of Geneva — Geneva School of Economics and Management (GSEM) and a postgraduate degree in Electrical engineering from EPFL, my work operates at the intersection of applied mathematics, engineering, and strategic decision-making. As a former Research Fellow at the Geneva School of Business Administration (HES-SO), I focus on solving complex industrial and societal problems.
My current research integrates operations research, stochastic optimization, and scientific machine learning. I apply these methodologies to drive biomedical data analysis, manufacturing engineering, and supply chain management.
This academic expertise is built on deep scientific foundations: prior to transitioning into management research, I spent over 20 years teaching advanced mathematics and physics in Switzerland and France, following an early career milestone as an associate member of the LHC project at CERN.
For detailed statements: Research Statement · Teaching Statement
Novel signal-to-image transformation for arrhythmia detection. CNN evaluated on 3 PhysioNet databases across 5 cross-database experiments. Published in Scientific Reports, Nature (2025).
View on GitHub → View paper →Graph-based EEG analysis for seizure detection, leveraging graphical signal representations and machine learning. Published in Biomedicines (2024).
View on GitHub → View paper →Novel PSO algorithm with exponential velocity dynamics for global optimization. Extended into ExPSO-DL, an open-source Python package for deep learning optimization. Published in IEEE Access (2022) and Journal of Open Research Software (2025).
IEEE Access paper → ExPSO-DL package →Research on digital technology adoption in dairy supply chains, focusing on waste management, traceability and resilience of the Gruyère AOP supply chain in Switzerland.
Optimized reverse logistics for hydrogen cartridges using CVRP, Simulated Annealing, and Genetic Algorithms. Focus on cost minimization and CO₂ reduction. In collaboration with STOR-H.
Optimization models for humanitarian relief networks integrating pre- and post-disaster factors. Decomposition model addressing uncertainties in relief operations.
Hierarchical forecasting integrating social media data and expert insights with a probabilistic inventory management model for short life cycle products.
Research on blockchain and IoT for hospital waste reverse logistics. Applied Best-Worst Method (BWM) and DEMATEL to prioritize technology adoption barriers.
Over 15 years of teaching Advanced Mathematics, Physics, Applied Mathematics, Algorithms, Chemistry, and Descriptive Geometry for Swiss Maturity and French Baccalaureate programs.
Notable: student project "An Ecological Outdoor Lighting System" received the Gold Medal at the International Exhibition of Inventions, Geneva.
Open to research collaborations and academic or industry positions.
Based in Switzerland (Geneva / Fribourg area). Available for opportunities in applied research, data science, operations research, and teaching.