Enrico Bibbona

Enrico Bibbona is an Associate Professor at the Department of Mathematical Sciences (DISMA) at Politecnico di Torino, where he contributes to the Interdepartmental Center SmartData@PoliTO - Big Data and Data Science Laboratory. His academic profile spans statistics, mathematical modeling, and data science applications across multiple engineering disciplines.

His primary research interests include:

• Asymptotic statistics
• Bayesian inference
• Biostatistics
• Industrial statistics
• Mathematical biology and modeling in life sciences
• Statistical inference for stochastic processes
• Stochastic modeling

His specific research lines focus on Reaction Networks approximation and inference, Statistical modeling of animal calls, Statistics and modeling for the SmartPad system (in collaboration with ITT), and Statistics for deterministic and stochastic dynamical models. His work bridges theoretical statistics with practical applications across various scientific domains, particularly in biological systems, industrial applications, and data science.

His notable recognition includes the Elsevier/SPA Travel Award presented by Elsevier and Bernoulli Society, Denmark (2011).

Professor Bibbona actively mentors PhD students across multiple programs, currently supervising Daniele Poggio and Saeed Sani in Mathematical Sciences, and has previously guided Elena Sabbioni (thesis: Statistical Methods for Complex Biological and Clinical Data) and Hiu Ching Yip (thesis: Statistical models for understanding biomedical data). His teaching spans Mathematical Engineering, Data Science and Engineering, and Communications Engineering programs, where he teaches courses including BioQuants, Statistical methods in data science, and Project: Software-defined communication systems.

He is a key member of the Statistics and Data Science research group at DISMA and has contributed to practical applications through patents including "BRAKING SYSTEM TEMPERATURE ESTIMATOR" and "A method for estimating the wear of a vehicle brake element," demonstrating his ability to translate theoretical work into real-world solutions.