SPECIAL SESSION #12
Probability, Statistics and Machine Learning for living environment and metrology
ORGANIZED BY
Antonella Iuliano
Antonella Iuliano
University of Basilicata, Italy
Pietro Liò
Pietro Liò
University of Cambridge, UK
Antonio Di Crescenzo
Antonio Di Crescenzo
University of Salerno, Italy
ABSTRACT
Probability Theory and Statistics provide powerful tools for developing new mathematical models to describe real-life phenomena. In particular, the use of metrology in the context of the living environment plays an important role in many applied fields, helping to understand and identify sources of variability and minimize their influence. The aim of this section is to address the gap in the application of probabilistic models, machine learning, and artificial intelligence in this area. One of the key advantages of using probabilistic models is that they provide a comprehensive view of the uncertainty associated with measurement results. Special attention will be given to outcomes related to the quality of the living environment, given its direct impact on human health and well-being.
ABOUT THE ORGANIZERS
Antonella Iuliano is a Researcher in Probability and Statistics at the University of Basilicata, Italy, and currently serves as a Visiting Researcher at the Department of Computer Science and Technology, University of Cambridge, UK. She completed her PhD in Mathematics in 2012 at the Department of Mathematics and Informatics, University of Salerno, Italy. She then worked as a post-doctoral researcher at the IAC-CNR in Naples, Italy, and held the position of Visiting Researcher at the University of Cambridge, UK. She also served as a Senior Mathematical Statistician in the Bioinformatics Core at the Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Italy. Her research is focused on the application of Probability and Statistics to Machine Learning (ML) and Artificial Intelligence (AI), with particular emphasis on precision medicine and healthcare. Currently, her research interests center on the development of stochastic processes based on finite-velocity random motions, as well as statistical models for integrating high-dimensional data, with applications across biology, medicine, and environmental sciences. She is actively involved in various projects and collaborations within the life sciences field, and her work has been widely published in international journals and conference proceedings.
Pietro Liò is a Full Professor at the Department of Computer Science and Technology, University of Cambridge, where he is also a member of the Artificial Intelligence Group. He is affiliated with the Cambridge Centre for AI in Medicine. His research focuses on developing Artificial Intelligence and Computational Biology models to understand the complexity of diseases and to address personalized and precision medicine. His current work centers on Graph Neural Network modeling. He holds an MA from Cambridge and two PhDs: one in Complex Systems and Nonlinear Dynamics from the School of Informatics and the Department of Engineering at the University of Firenze, Italy, and another in (Theoretical) Genetics from the University of Pavia, Italy. He is a member of several prestigious committees, including the committee for the MPhil in Computational Biology (Stakeholder Group for the CCBI), the steering committee of Cambridge BIG Data, and VPH-UK (Virtual Physiological Human). He is also a Fellow and member of the Council of Clare Hall College, as well as a member of Ellis, the European Lab for Learning & Intelligent Systems. Additionally, he is a member of the Academia Europaea and is listed on www.topitalianscientists.org.
He serves as a member of the Complaint Officer/Examination Review Committee at Cambridge University and is a reviewer for four MPhils (Newcastle University). He is also part of the steering committee of VPH-UK. He has authored over 400 scientific publications in international journals and conference proceedings.
Antonio Di Crescenzo is Full Professor at the Department of Mathematics of the University of Salerno, where he is also a member of the Advisory Board of the Graduate School in Mathematics. From September 2020 he is the head of the PRISMA Group (Probability In Statistics, Mathematics and Applications) of the Italian Mathematical Union. He is the head of the Research Unit of the University of Salerno for the PRIN-2017 project "Stochastic Models for Complex Systems" (2019-2023) funded by MIUR. His research interests include stochastic modeling, theory and simulation of stochastic processes with applications to biomathematics, queueing systems, reliability theory, aging notions and information measures. He held various research periods abroad, mainly in Spain, Japan, USA. He is the author of about 100 publications, appearing mainly in international journals and Proceedings of International Meetings. He co-organized several International Meetings and participated in more than 60 international scientific meetings, specially in applications of probability, in biomathematics and biocybernetics. He is member of the Editorial Board of various international journals.
