I grew up in Trentino, surrounded by mountains and at the crossroads of Central and Southern Europe.
From an early age and thanks to my parents, I developed a strong sense of curiosity and an instinct to step beyond what feels familiar to explore, learn, and constantly challenge myself.
Study and sports are the two main activities that filled my youth, I pushed myself to excel at school just as much as I did on the ski slopes.
I studied Industrial Engineering in Trento before spending an Erasmus semester at TU Wien, where I learned not only how to study in an international environment,
but also how to live in a large, multicultural city. I then pursued a Master’s degree in Mechanical Engineering at Politecnico di Milano, one of Europe’s leading technical universities,
specialising in materials and manufacturing. During the studies I also attended courses and interships with Brembo, European Space Agency (ESA) and Siemens.
My thesis was about a load monitoring system for aeronautical structures, verified numerically and experimentally. It later became a journal publication.
After graduating I felt I needed to go abroad again, that's why I became a resident engineer for Industrie Saleri Italo, located at the
BMW Motoren plant in Steyr. I spent almost four years helping the italian and BMW team designing and industrialising thermal management
systems and water pumps, from first concept to series production.
In the meantime I was getting more and more into coding, maths and statistics and by chance during a coffee break I discovered that at the JKU in Linz offered
a master's in artificial intelligence. I enrolled without hesitation and attended courses while working full
time. I really enjoyed the possibility to refresh and learn about mathematics, statistics, machine learning, deep learning, generative models, as well as tutoring the
"Hands on AI" course. Average grade Sehr gut.
Since June 2023 I have been the lead data scientist in the central manufacturing department at
thyssenkrupp Automotive in Liechtenstein. Computer vision on assembly lines, anomaly detection at
the scale of millions of datapoints per day, an on-premise RAG assistant over the company wiki, hybrid
physics/ML models that cut scrap, Bayesian networks for uncertainty quantification. End to end, every time:
acquisition, storage, labelling, model, validation, deployment, monitoring. I have also helped shape the
company's digital transformation and AI strategy, collaborated with FH Vorarlberg and OST, supervised a
master's thesis as industrial tutor, and represented the company at Bodenseegespräche 2024 and ICML 2024 in
Vienna.
