About Fabio
Italian
Native or bilingual
English
Fluent
Dutch
Basic
Experience
- Self-EmployedPrincipal AI Consultant & Data ScientistOctober 2023 - Today (2 years and 8 months)• Develop AI strategies, design AI projects, write subsidies applications & secure funds• Production-ready prototyping of AI and automation solutions• Give talks on AI to general audiences and experts of other domains• Developing an application for audio classification at scale• Data processing and analysis for process engineering
- In Ovo | Join our team!Data ScientistBIOTECHApril 2022 - Today (4 years and 2 months)Leiden, NetherlandsBusiness: determine sex of eggs to avoid male chicken cullingRole:• First data scientist hired by the company• End-to-end development of automated analytical report generator• Ideate and co-develop anomaly detection dashboard via asymmetry detection• Increase predictive model performance by 25% via improving data quality
- Machine2LearnSenior Data ScientistDIGITAL AND ITApril 2018 - March 2022 (3 years and 11 months)Amsterdam, NetherlandsCompany: develop AI solutions for industrial and academic customersRole:• Joined in the 7th month of this boutique AI consulting company as employee number 5• Internal lead of EU projects on AI & healthcare: Prime (https://prime-study.eu) and Aggressotype (https://www.aggressotype.eu - completed)• Lead writer of scientific grants (two H2020 proposals accepted), tenders, technical documents, and business proposals; presenter to external academic and industrial audiences• Support design of Applied Data Science MSc program• Save on tech upgrade budget via demand forecasting via AI https:// machine2learn.com/use-cases/demand-forecasting-tmobile/• Save 15%+ on manual operation via solving advanced optimal mixture problems - https://machine2learn.com/use-cases/process-optimisation akzonobel/• Design & implement causal discovery software• Successfully develop real-time processing pipeline for data streamed from wearables• Successfully develop an analytical framework for image processing algorithm evaluation• Exploratory data analysis for business case development• Unit testing (R) and property-base automated testing (Python)• Biomedical data integration and bias compensation• Successfully generate realistic artificial data based on domain expert knowledge and literature research• Deep learning (Keras&Tensorflow)• Develop classification and regression models
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Education
- Doctor of Philosophy (PhD), Machine Learning & BioinformaticsRadboud University Nijmegen2012Doctor of Philosophy (PhD), Machine Learning & Bioinformatics
- Master Degree (Laurea Vecchio Ordinamento), MathematicsUniversità di Pisa2007Master Degree (Laurea Vecchio Ordinamento), Mathematics
Certifications
- Neural Networks and Deep LearningCoursera2018