Tommaso Alfonsi is a Data & Software Engineer with a PhD in Information Technology and a decade of experience applying machine learning, statistical modeling, and big data engineering to genomic problems. Currently a postdoctoral genomic data scientist at Politecnico di Milano and recently joining Motus ml, he builds production-ready data pipelines and computational methods for viral and human genomics using Python and modern frameworks. His work spans academia and applied engineering—from developing a pathogen data warehouse to teaching hands-on software courses for bioinformatics and engineering students. Trained also at the University of Oxford in AI, he combines rigorous research methodology with practical software design to translate complex biological datasets into actionable insights. Colleagues note his ability to move projects from prototype to deployable systems, often bridging domain science and scalable data architectures.
10 years of coding experience
3 years of employment as a software developer
Master Intelligenza artificiale, Master Intelligenza artificiale at University of Oxford
Doctor of Philosophy - PhD Information Technology, Doctor of Philosophy - PhD Information Technology at Politecnico di Milano
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