Riccardo Zese is an assistant professor and member of the research group on Machine Learning and Artificial Intelligence at the University of Ferrara. His work mainly focuses on the development of inference and machine learning techniques for probabilistic logics, the combination of logics with different semantics into hybrid structures and the study of neuro-symbolic techniques (neural networks plus logic). Riccardo Zese is the author of more than 60 peer reviewed articles in the areas of Machine Learning, Inductive Logic Programming and Statistical Relational Learning.

The complete CV can be found at the following link.

Short Curriculum

Riccardo Zese's PhD thesis was awarded an honourable mention at the EurAI Distinguished Dissertation Award 2016 and is published as a monograph entitled "Probabilistic Semantic Web - Reasoning and Learning", published by IOS Press Amsterdam with AKA Verlag Berlin. His work on one of the systems described in his thesis won the best paper award at the 2013 RR International Conference in Mannheim. Riccardo Zese (RZ) is the author of more than 60 peer-reviewed papers.

RZ has given two invited talks at the International Joint Conference on Artificial Intelligence (IJCAI), one of the world's leading artificial intelligence conferences (A++ classification). He has also given five tutorials, two of which were invited, at international conferences and workshops.

RZ was co-chair for the international conference ILP 2018 and the international workshop PLP 2017 and organised the Summer School on Statistical Relational Artificial Intelligence, an Advanced Course on AI (ACAI 2018) sponsored by EurAI and the international conference AIxIA 2015. In addition, he is a member of the programme committee of IJCAI (of which he was also a member of the senior programme committee), AAAI, ECAI, NeurIPS, ICML, KR, UAI, ICLR, ECML PKD, ILP, ICLP, LOD, RuleML+RR, IJCLR, AmI, AIxIA. RZ is a member of the editorial board of Intelligenza Artificiale, the official journal of the Italian Association for Artificial Intelligence. He is on the editorial board of Frontiers in Machine Learning and Artificial Intelligence and Frontiers in Robotics and AI, specialty section on Computational Intelligence.

RZ has collaborated with international research groups on projects related to probabilistic logics and has been in charge of the working unit related to automatic classification and prediction of leaks, and user profiling, within the GST4Water project (Green Smart Technology for Water,, funded by the POR FESR 2014-2020 within the Intelligent Specialization Strategy), and of the working unit related to automatic recognition from images of lot numbers and expiration dates of food products within the SORT project ("Development of innovative integrated technological systems for the unpacking, organisation of stocks and tracking of wasted food products aimed at their valorisation", financed within the framework of the National Operational Programme for Research and Competitiveness 2007-2013, Smart Cities and Communities and Social Innovation, Axis II - Support for innovation, Operational Objective - Integrated actions for sustainable development and the development of the information society).

He has participated in the research activities of the POLIS-EYE project (POLIcy Support systEm for smart citY data governancE,, an industrial research project financed by POR FESR Emilia-Romagna 2014-2020 within the framework of the Intelligent Specialisation Strategy (S3), of which the MechLav laboratory, of which he is a member, is a partner together with the GeoSmart Lab, CIRI ICT, ENEA CROSS-TEC, and AIRI laboratories. The POLIS-EYE project aims to develop a decision support system (Policy Support System) mainly addressed to public decision-makers, for the optimised management of Smart Cities in the field of tourism. He also participated to the European project ePolicy (Engineering the POlicy- making LIfe Cycle,, active within the call FP7-ICT-2001-7, project code: 288147, and in the project (IA4I4) Automatic analysis of Big Data for Industry 4.0, co-funded by the University of Ferrara and the Chamber of Commerce Ferrara (resp. Prof. E. Lamma). RZ has also participated in the activities of the industrial research project PolisEye (POLIcy Support systEm for smart citY data governancE, funded by the POR FESR Emilia Romagna 2014-2020 within the framework of the Intelligent Specialisation Strategy (S3), and of the regional project Supercomputing Unified Platform - Emilia-Romagna (SUPER) funded within Action 1.5.1, by the POR-FESR 2014-2020 Emilia Romagna.

He currently holds the National Scientific Qualification in the sectors 09/H1 and 01/B1, both in tier II.

Since A.A. 2019/2020 he has been lecturer in a Master's degree course on Deep Learning at the Department of Engineering. From A.Y. 2020/2021 he is lecturer of the course "Mathematics and Computer Science" and head of the aggregate course of "Mathematics, Computer Science and Physics" at the Department of Chemical, Pharmaceutical and Agricultural Sciences, for the degree course in Agricultural Technologies and Aquaculture of the Delta.