Summary
Simone Silvetti is a researcher and software engineer based in Trieste with a PhD in Computer Science and over a decade of experience developing algorithms and production software for numerical methods, optimization, and process mining. He has led R&D efforts at ESTECO building ETL pipelines, time-series analysis, Gaussian Process and Bayesian optimization implementations, and contributed to ADAS verification via active learning. As a former scrum master and adjunct professor, he bridges rigorous academic research with pragmatic software delivery and teaching, often translating prototypes into Java production components. Notably, he combines deep mathematical training (MSc and BSc with top honors) with hands-on experience integrating numerical libraries and IoT data streams, making him adept at turning complex models into scalable, customer-facing features.
11 years of coding experience
10 years of employment as a software developer
Ph.D. in Computer Science, Computer science, Ph.D. in Computer Science, Computer science at Università degli Studi di Udine
Master of Science (MSc), Analysis, Mathematical physics, 110/110, Master of Science (MSc), Analysis, Mathematical physics, 110/110 at La Sapienza University, Rome, Italy.
English, Italian