Zurich, Zurich, Switzerland
Scientist with an interdisciplinary background in Physics, Engineering, and Data Science, and international experience in both private and public sectors across Italy, the USA, and Switzerland. Experienced in managing research projects and leading international research teams. MANAGEMENT SKILLS • Scientific research project management (10+ years) • Leadership of international research teams (up to 5 people; 5+ years) TECHNICAL SKILLS • Semiconductor physics; micro- and nano-technology (10+ years) • Vacuum and cryogenic technology (11+ years) • Device physics simulation and modeling (6+ years) • Programming (13+ years): Python expert, experienced with C, Matlab, Spark, SQL, Pascal, Visual Basic • Artificial Intelligence (3+years): neural networks, CNNs, Bayesian optimization, Transformers
• Leading AI R&D projects on Electrical Discharge Machining (EDM) — developed a hardware/software framework for autonomous self-optimizing EDM, demonstrating 30% productivity improvement on representative test cases (Innosuisse Avagama 104.215 IP-ENG); released open-source Bayesian Optimization library (GitHub); organized workshop on AI methodologies for EDM; acquired ca. 1.2M CHF in funding for research activities.
• Researcher on AI for imaging — Developed generative deep-learning models and GUI for MRI imaging, targeting 50% reduction in contrast agent dose; built 2D/3D segmentation algorithms for optical and CT volumetric data using CNNs and transformer architectures (Innosuisse 63342.1 INNO-L).
• Project lead on quantum dot devices (EU H2020 TeTra) — led design, nanofabrication, and characterization of quantum dot devices for thermoelectric transport studies, coordinating a team of researchers; secured ~200k CHF in funding (Marie Skłodowska-Curie Grant Agreement 754364) and delivered EU milestone report. • Project lead (SNF 182544) on solid-state heterostructures — led and contributed hands-on to device design, micro/nanofabrication, and electro-optical characterization; developed novel diode architectures based on van der Waals heterostructures; published 6 peer-reviewed articles. • Researcher on molecular devices (EU H2020 QuIET) — characterized thermoelectric properties of molecular junctions; developed a thermoelectric measurement methodology for nanodevices; released open-source measurement and data analysis toolkit; co-organized MSCTT2020 international conference (Engelberg, CH, Jan 2020); published 1 peer-reviewed article.
• Researcher on non-thermal plasma-assisted catalysis for NH3 synthesis (US ARO) — designed and operated plasma reactors; elucidated reaction mechanisms through experiments and molecular dynamics simulations; published 1 peer-reviewed article. • Researcher on synthesis of Si quantum dots via non-thermal plasmas – Produced internal reports (confidential).
• AI Researcher on electric consumption forecasting: developed and validated an FPCA framework for short- and long-term prediction on a dataset of 3,500+ MV/LV substations across Milan's metropolitan area; outperformed all benchmark methods on an international competition dataset (MAPE 4.7% vs 7.0%); published 1 peer-reviewed article; released open-source code (GitHub).