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Dr. Alessio Benavoli

Associate Professor (Statistics)

 ALESSIO.BENAVOLI@tcd.ie

 


Biography

Alessio Benavoli is an internationally recognised researcher in statistics, probabilistic machine learning, and automation. He received his Master's degree (2004) and his Ph.D. (2008) in Computer and Control Engineering from the University of Florence, Italy. From 2007 to 2008, he worked for the international company SELEX-Sistemi Integrati as system analyst. From 2008 to 2019, he was at the Dalle Molle Institute for Artificial Intelligence (IDSIA) in Lugano, Switzerland, becoming full professor in 2018. From 2019 to 2021, he was Senior Lecturer in Artificial Intelligence and Machine Learning (ML) at the University of Limerick (Ireland). Currently, he is Associate Professor in Statistics at the School of Computer Science and Statistics, Trinity College Dublin. Alessio has ~130 technical peer-reviewed publications in main scientific journals and conferences in AI, machine learning (ML) and statistics, and his research bridges AI and ML, data science and engineering. He has 16 years experience in developing statistical models and AI-based systems for industry with applications to smart manufacturing, quantitative finance, green energy production forecast and defence sector.

Research Tags

  Artificial Intelligence/Cybernetics   Control Theory (Computer Sciences)   Data Analysis   Probabilistic Machine Learning   Probability   Quantum information physics   Statistics

Research Projects

 Humans-in-the-Loop towards a more effective AI in manufacturing
 Data analytics for the development of smart infusion pumps

Alessio Benavoli and Dario Azzimonti and Dario Piga, Learning Choice Functions with Gaussian Processes, Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence, edited by Robin J. Evans and Ilya Shpitser , 216, PMLR, 2023, pp141--151 , Conference Paper, PUBLISHED
Alessio Benavoli and Dario Azzimonti and Dario Piga, Bayesian Optimization For Choice Data, 2023 Genetic and Evolutionary Computation Conference Companion (GECCO '23 Companion), July 15--19, 2023, Lisbon, 2023, Conference Paper, PUBLISHED  DOI
Arianna Casanova and Alessio Benavoli and Marco Zaffalon, Nonlinear desirability as a linear classification problem, International Journal of Approximate Reasoning, 152, 2023, p1-32 , Journal Article, PUBLISHED  DOI
Ristic, Branko and Benavoli, Alessio and Arulampalam, Sanjeev, Credal Valuation Networks for Machine Reasoning Under Uncertainty, IEEE Transactions on Artificial Intelligence, 2023, p1-10 , Journal Article, PUBLISHED  DOI
Branko Ristic and Alessio Benavoli and Alex Skvortsov, Robust target area search using sets of probabilities, Digital Signal Processing, 142, 2023, p104195 , Journal Article, PUBLISHED  DOI
Arash Kia and James Waterson and Norma Bargary and Stuart Rolt and Kevin Burke and Jeremy Robertson and Samuel Garcia and Alessio Benavoli and David Bergström, Determinants of Intravenous Infusion Longevity and Infusion Failure via a Nonlinear Model Analysis of Smart Pump Event Logs: Retrospective Study, JMIR AI, 2, 2023, pe48628 , Journal Article, PUBLISHED  DOI
Enrique Miranda, Ignacio Montes, Erik Quaeghebeur, Barbara Vantaggi(ed.), Closure operators, classifiers and desirability, 2023, Proceedings of a Conference, PUBLISHED
Alessio Benavoli and Alessandro Facchini and Marco Zaffalon, Quantum indistinguishability through exchangeability, International Journal of Approximate Reasoning, 151, 2022, p389-412 , Journal Article, PUBLISHED  DOI
EANNA McGRATH, NICK MAHONY, NEIL FLEMING, ALESSIO BENAVOLI, and BERNARD DONNE, Prediction of Functional Threshold Power from Graded Exercise Test Data in Highly-Trained Individuals, International Journal of Exercise Science, 15, (4), 2022, p747 - 759, Journal Article, PUBLISHED
Almardeny, Yahya and Benavoli, Alessio and Boujnah, Noureddine and Naredo, Enrique, A Reinforcement Learning System for Generating Instantaneous Quality Random Sequences, IEEE Transactions on Artificial Intelligence, 2022, p1-1 , Journal Article, PUBLISHED  DOI
  

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Research Interests

Description Of Research Interests

My main research interests are in the areas of Bayesian parametric and non-parametric statistics; foundation of probability theory and desirable gambles; quantum mechanics; decision-making under uncertainty; prior near-ignorance; dynamical systems and control; with applications to data analytics, machine learning and control theory.