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Dr. Alessio Benavoli

Associate Professor (Statistics)


  Artificial Intelligence/Cybernetics   Control Theory (Computer Sciences)   Data Analysis   Probabilistic Machine Learning   Probability   Quantum information physics   Statistics
Benavoli, A.; Azzimonti, D.; Piga, D., Skew Gaussian processes for classification, Machine Learning, 109, 2020, p1877 - 1902, Journal Article, PUBLISHED
Ristic, B.; Gilliam, C.; Byrne, M.; Benavoli, A., A tutorial on uncertainty modeling for machine reasoning, Information Fusion, 55, 2020, p30 - 44, Journal Article, PUBLISHED
Piga, D.; Bemporad, A.; Benavoli, A., Rao-Blackwellized sampling for batch and recursive Bayesian inference of Piecewise Affine models, Automatica, 117, 2020, Journal Article, PUBLISHED
Schürch, M.; Azzimonti, D.; Benavoli, A.; Zaffalon, M., Recursive estimation for sparse Gaussian process regression, Automatica, 120, 2020, p109 - 127, Journal Article, PUBLISHED
Benavoli, A. ; Facchini, A. ; Zaffalon, M., Bernstein's socks, polynomial-time provable coherence and entanglement, PJMLR, International Symposium on Imprecise Probability: Theories and Applications, Ghent, Belgium, edited by Bock, De J; de Campos, C; de Cooman, G; Quaeghebeur, E; Wheeler, G , 2019, Conference Paper, PUBLISHED
Piga, D. ; Benavoli, A., Semialgebraic Outer Approximations for Set-Valued Nonlinear Filtering, European Control Conference (ECC), Naples, Italy, 25-28 June , 2019, Conference Paper, PUBLISHED
Alessio Benavoli, Alessandro Facchini, Dario Piga, Marco Zaffalon, Sum-of-squares for bounded rationality, International Journal of Approximate Reasoning, 2019, p130 - 152, Journal Article, PUBLISHED
Benavoli, A; Balleri, A; Farina, A, Joint Waveform and Guidance Control Optimization for Target Rendezvous, IEEE Transactions on Signal Processing, 67, (16), 2019, p4357 - 4369, Journal Article, PUBLISHED
Benavoli, A. , Dual Probabilistic Programming, ROBPROG 2018 The International Conference on Probabilistic Programmin, MIT, Boston, US, 2018, Conference Paper, PUBLISHED
Benavoli, A.; Facchini, A. ; Piga, D.; Zaffalon, M. , SOS for bounded rationality, Proc. ISIPTA'17 Int. Symposium on Imprecise Probability: Theories and Applications, , 2017, Conference Paper, PUBLISHED

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My current research interests lie in Bayesian statistics and probabilistic machine learning. Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the main theoretical and practical methodologies for designing machines that learn from data. My research on this topic focuses on nonparametric models, decision making under uncertainty, and reliability and risk analysis. I am also interested in control theory, signal processing, and the foundation of rationality theories including probability and quantum theory. I have 15 years experience in developing statistical models and AI-based systems for industry with applications to smart manufacturing, quantitative finance, green energy production forecast and defense sector.