Machine and Deep Learning, Big Data Analytics, Data and Process Mining, Sentiment Analysis, Predictive Maintenance
Research focuses on the whole end-to-end data analysis process that leads to knowledge discovery from heterogenous raw operational data. In particular, methodologies have been developed for pre-processing and feature extraction, machine learning for unbalanced data and cost-sensitive classification, deep learning in the emerging fields of process discovery from event logs and sentiment analysis. Examples of application fields are: predictive maintenance, analysis of social media data and reviews, customer behaviour analysis, trajectory analysis, process outcome prediction.
Data Analytics, Artificial Intelligence and Cybersecurity (DAISY)
Technische Universiteit Eindhoven, Université de Bordeaux, UHP Nancy 1, University of Dayton, Bremer Institut für Produktion und Logistik GmbH (BIBA), CNR, BOC Group AG, ATOS Spain SA, AIDIMA Association, DBpedia Association, Regione Marche, Dipartimento della Pubblica Sicurezza, BIESSE Spa, Iveco Group NV, Magazzini Gabrielli Spa, Engineering Ingegneria informatica Spa, YKK Spa, Loccioni Group, Namirial Spa, Pluservice Srl, Mediamente Consulting Srl, ETT Spa
Claudia Diamantini, Domenico Potena, Emanuele Storti, Davide Manzoni, Alex Mircoli