Summary
Marco Podda is an assistant professor and machine learning researcher with eight years of experience focused on deep learning for graphs and generative models applied to biomedical problems. Based at the Università di Pisa and Tuscany, he progressed from PhD research on clonal evolution data to a visiting scientist role in computational vaccinology at GSK, bridging academic rigor with industry-scale data science. His work combines generative modelling and graph-based methods to tackle complex biomedical datasets, with a practical eye toward translational impact. Known for blending theory and application, he brings hands-on experience in both academic research and industrial collaboration, and a track record of turning biological questions into machine learning solutions.
8 years of coding experience
2 years of employment as a software developer
Laurea triennale, Informatica, 99, Laurea triennale, Informatica, 99 at Università degli Studi di Cagliari
Laurea Specialistica, Informatica, 104/110, Laurea Specialistica, Informatica, 104/110 at Università di Pisa
Italian, English, French, Spanish