Riccardo Zese is an Associate Professor at the Department of Chemical, Pharmaceutical, and Agricultural Sciences and a member of the AI@UniFE Artificial Intelligence research group at the University of Ferrara, where he has been affiliated since 2012. His research focuses on probabilistic reasoning, machine learning, and deep learning, with a particular interest in integrating logics with diverse semantics into hybrid structures and advancing neuro-symbolic techniques that combine neural networks with logic. This specialization is rooted in his extensive background in inference techniques and machine learning for probabilistic logic. Since January 2016, he has served as a Postdoctoral Research Fellow in the Department of Engineering at the University of Ferrara. He received his Ph.D. in Computer Science from the University of Ferrara in April 2016 and his Laurea in Computer Engineering in July 2012. 

Prof. Zese is a member of AI*IA (AI*IA – Associazione Italiana per l’Intelligenza Artificiale) and GULP (Gruppo Ricercatori e Utenti Logic Programming). Additionally, he is a passionate homebrewer and an ANAG-certified taster. He has authored over 80 peer-reviewed articles in fields such as machine learning, inductive logic programming, and statistical relational learning.

For a complete list of publications see: Publications on University Webpage, Google Scholar, Semantic Scholar, Loop, DBLP, ORCID, Scopus, WOS, Academia, Kudos, ResearchGate, AMiner, SciProfile 

For a full version of curriculum vitae, see: Full Curriculum Vitae

AIDA4Edge | Twinning for Excellence in Adaptive Edge AI, 2024-2027

• Funded by: Twinning Bottom-Up (HORIZON-CSA, Call: HORIZON-WIDERA-2023-ACCESS-02 - Topic: HORIZON-WIDERA-2023-ACCESS-02-01)  

• Role: WP leader and UniFE Unit Leader

• Keywords: Artificial intelligence, intelligent systems, multi agent systems, Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video), Scientific computing and data processing, Signal processing, Edge AI, Compression of Neural Network, Quantization, Artificial Neural Networks, Resource-constrained Edge Devices

• Duration: 36 months

• Partners:

  • University of Niš  - Faculty of Electronic Engineering (FEEUNI) - Project Leader

  • IHP GmbH - Innovations for High Performance Microelectronics 

  • University of Manchester

• Abstract: The main goal of AIDA4Edge is to strengthen networking between the Coordinator (FEEUNI) and the advanced partners (IHP, UoM and UNIFE) from European institutions in order to enable FEEUNI to reach scientific and innovation excellence in the field of Edge AI (Artificial Intelligence). Fundamental and thriving research will tackle the issue of bringing complex AI algorithms to Edge devices with resource constrains in terms of memory, processing power, energy consumption and latency. To meet this challenge, the synergy of expertise of all partners will be exploited and an adaptive AI-enabled edge computing pipeline will be developed. UNIFE will contribute with the expertise in the field of optimization and tuning hyperparameters of ANN (Artificial Neural Network) utilizing probabilistic logic. IHP will be in charge of exploiting the advantages brought by multi-core AI accelerators in terms of power consumption and reliability. UoM will leverage the synergies between bio-inspired SNNs (Spiking Neural Networks) and ANNs, to maintain the accuracy of conventional ANNs and to exploit the input data sparsity through the asynchronous computational capabilities of bio-inspired SNNs. FEEUNI will bring the expertise in quantization, important for ANN compression and resource saving. By the knowledge transfer and the exchange of the best practice, networking will provide FEEUNI all knowledge it lacks. It will enable FEEUNI not only to empower research capacity, but also to become the center of excellence in the field of Edge AI and to raise the reputation and enhance research management capacities and administrative skills. This will strengthen and encourage FEEUNI team (with a lot of women involved) to apply to variety of new research calls and to boost progress in science and economy in Serbia and beyond, reducing the imbalance of research capabilities between developed European countries and Serbia.

THERE | auTomatic HElpeR for cEphalometry, 2016-2018

• Funded by: 5X1000 contribution, year 2020 

• Role: Principal Investigator

• Keywords: Machine Learning, Computer Vision, Artificial Intelligence, Odontology, Diagnostic Methods and Tools

• Duration: 12 months

• Description: The aim of this project is to apply image processing, machine learning and computer vision techniques for the automatic identification of landmarks necessary to define the cephalometric tracing, performed on a teleradiograph taken in latero-lateral projection with the dental arches in maximum intercuspation. This tracing is used for the diagnosis of various pathologies, including malocclusion. The ultimate goal is to develop a software, THERE (auTomatic HElpeR for cEphalometry), which exploits a predictive model that analyses teleradiographs and returns the coordinates of the affected points with the highest possible accuracy. These coordinates will then be used by THERE to automatically calculate significant angles and deliver the diagnosis to the doctor.

GST4Water | Green Smart Technology for Water, 2016-2018

• Funded by: Regione Emilia-Romagna (POR-FESR2014-20), within the Smart Specialization Strategy (S3) and the Cohesion Development Fund 

• Role: Work Unit Leader (OR2)

• Keywords: Artificial intelligence, intelligent systems, multi agent systems, Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video), Scientific computing and data processing, Signal processing, Edge AI, Compression of Neural Network, Quantization, Artificial Neural Networks, Resource-constrained Edge Devices

• Duration: 36 months

• Partners:

  • Research Labs: Terra & Acqua Tech, LEA ENEA, CIRI-EA, CIRI-EC 

  • Industrial Partners: CADF, SOGESE, XEO4, STARPLAST, VerdeAlto 

• Description: The project aimed at developing innovative solutions towards economical savings and hydro-sustainability by means of ICT technologies that should make citizens informed about water consumption.  See the following publication: IEEE Access

SORT | Sviluppo di sistemi tecnologici innovativi integrati per lo Spacchettamento, l'Organizzazione delle scorte e il Tracciamento dei prodotti alimentari sprecati finalizzati alla loro valorizzazione , 2024-2027

• Funded by: Italian MUR on Axis II of the National operative programme (PON) for Research and Competitiveness 2007-13 within the call ‘Smart Cities and Communities and Social Innovation’ (2014-15)  

• Role: Work Unit Leader (OR2.4)

• Duration: 24 months

• Partners: University of Parma, TSP-Tecnologie e Servizi Professionali S.r.l., Plastic Sort S.r.l., Alfacod S.r.l., Curti Costruzioni Meccaniche S.p.A.

• Description: The aim of the project is the management of expired or discarded food products for conversion into feed, fertiliser and general reuse wherever possible.

• Objectives: The project is structured into four Objectives (ORs): development of technologies for real-time monitoring of indoor and outdoor water consumption (OR1); creation of a platform for processing and communicating water consumption to managers and users (OR2); creation of systems for the management, recovery and reuse of rainwater and grey water on a building scale (OR3); development of tools for assessing the economic-environmental sustainability of urban water systems (OR4). 

S4C | Support System for Sustainable Smart Cities, 2024- 2026

Support System for Sustainable Smart Cities addresses the environmental impact of tourism and transportation—two sectors that together contribute significantly to CO₂ emissions—S4C builds on previous project POLIS-EYE to create a platform for optimizing mobility flows in tourism-heavy areas, with initial case studies focused in Bologna and scalable to other regions. S4C aims to support sustainable planning by integrating transport solutions, using “what-if” scenarios for strategic decision-making, and creating a shared data space to provide valuable insights for businesses, policymakers, and tourists.

AI&BM4Leukemia | Artificial Intelligence and Biophotonic Microscopy for rapid and early tests in Leukemia cells, 2023- 2024

AI&BM4Leukemia, financed by the IFAB (International Foundation Big Data and Artificial Intelligence for Human Development) programme year 2022, focuses on the use of machine and deep learning algorithms to create innovative tests for the rapid and early recognition of aberrant leukaemic cells to accelerate diagnostic and prognostic analysis, including response or resistance to therapies.

MIRC.0 | Sviluppo di un’intelligenza artificiale per favorire la sostenibilità della spesa corrente delle famiglie e l’affidabilità dei crediti (Macchina Intelligente Recupero Crediti ver. 0), 2022- 2024

MIRC.0 aims at the realisation of a decision-support system, based on artificial intelligence tools, capable of improving dialogue and shortening the distance between individuals and companies or administrations, in the context of credit protection and for the support of current household expenditure.

AI4MentalHealth | Intelligenza Artificiale per Predizione Diagnostica, di Carico Assistenziale, e di Esito: 40 Anni di accessi Presso i Centri di Salute Mentale della Provincia di Ferrara (AI4MentalHealth), 2021- 2022

Funded by FIR 2021 program, AI4MentalHealth, the project aimed at describing the epidemiological characteristics of users accessing territorial mental health services over the last 40 years, building and evaluating the capabilities of Machine Learning models to predict the mode and period of utilisation of healthcare resources by exploiting public health and socio-demographic data in order to identify diagnostic, care burden and outcome predictors.

SUPER | Supercomputing Unified Platform - Emilia Romagna, 2019- 2022

SUPER is an Emilia Romagna regional project financed under Action 1.5.1, by POR-FESR 2014-2020 Emilia-Romagna. The aim of this proposal is to create the prototype of a digital infrastructure, enhancing and federating the services offered by CINECA and INFN and subsequently extending them to those of ENEA, CMCC and in perspective of INAF and INGV.

POLIS-EYE | POLIcy Support systEm for smart citY data governancE, 2019-2022

POLIcy Support systEm for smart citY data governancE (POLIS-EYE), 2019-2022, financed by Regione Emilia-Romagna (POR-FESR2014-20). Participant. The project intended to analyze, together with companies, requirements and data related to the tourism sector to create forecasting and decision-making models integrated into a decision support system. See the following publications: LOD2021, ISC2, Predicting the impact of public events and mobility in Smart Cities, accepted for publication.

ePolicy | Engineering the POlicy- making LIfe Cycle, 2011- 2014

Engineering the POlicy- making LIfe Cycle,  in collaboration with the University of Bologna, Regione Emilia-Romagna, ASTER, University College Cork, Fraunhofer Institute for Computer Graphics Research, The University of Surrey, PPA ENERGY, Instituto De Engenharia De Sistemas E Computadores Do Porto, approved and financed under the call FP7-ICT-2001-7, project code: 288147. http://epolicy-project.eu/node 

• Member of the Editorial Board of Intelligenza Artificiale, the official journal of the Italian Association for Artificial Intelligence

• Member of the Editorial Board of Journal of Computer Science

• Review Editor for Frontiers in Robotics and AI, specialty section on Computational Intelligence

• Review Editor for Frontiers in Machine Learning and Artificial Intelligence

• Member of the Editorial Board of Advances in Computer Science

• Member of the Advisory Board of International Journal of Information Management and Technology

• Program co-chair of

  • ILP 2023 with Francesca A. Lisi and Elena Bellodi

  • ILP 2018 with Fabrizio Riguzzi and Elena Bellodi

  • PLP 2017 with Christian Theil Have

• Local organizer of

  • ACAI 2018

• Program Committees: IJCAI2025, IEEE MilCom 2024, ECAI2024, UAI2024, IJCAI2024, CILC2024, LOD2023, UAI2023, IJCAI2023, KR2023, CILC2022, LOD2022, ICML2022, AAAI2022, IJCAI2022, ICLR2022, LOD2021, PLP2021, RuleML+RR2021, CILC2021, IJCLR2021 (ILP 2021), IJCAI2021 (Senior PC member), AAAI2021, ICLR2021, PLP2020, RuleML+RR2020, IJCAI-PRICAI2020, AAAI2020, ICLR2020, ILP2020, RuleML+RR2019, IJCAI2019, AAAI2019, ILP2019, ICLR2019, IJCAI-ECAI 2018, AmI 2018, NIPS 2018, PLP 2018

• Member of the Organising Committee of

  • AI*IA 2015

• Reviewer for the PRELUDIUM grant, a funding scheme intended for young researchers who, by the proposal submission deadline, have not obtained a doctoral degree, financed by the National Science Center of Poland, 2019.

• Author of the book Probabilistic Semantic Web: Reasoning and learning, published by AKA-Verlag & IOS Press in the series Studies on the Semantic Web. ISBN: 978-1-61499-733-7, e-ISBN: 978-1-61499-734-4

• Honourable mention for the EurAI Distinguished Dissertation Award 2016 for the PhD Thesis titled “Probabilistic Reasoning and Learning for the Semantic Web”.

• Best Paper Award for “BUNDLE: A Reasoner for Probabilistic Ontologies”
  by Riccardo Zese, Fabrizio Riguzzi, Evelina Lamma and Elena Bellodi at the 7th International Conference on Web Reasoning and Rule Systems (RR-2013)

• Invited talk PLP: a brick to build your own starship at PLP 2018

• Invited tutorial Probabilistic Logic Languages and Their Combination at CILC 2018

• Tutorial Probabilistic Knowledge Representation in Machine Learning at AI*IA 2018

• Tutorial Learning from knowledge graphs at EKAW 2018

• Tutorial Probabilistic Description Logics: Reasoning and Learning at RuleML+RR 2017

• Member of the Joint Teachers-Students Committee ("Commissione Paritetica Docenti-Studenti") for the interclass Master's degree course in Artificial Intelligence, Data Science and Big Data of the Departments of Engineering and Mathematics and Computer Science of the University of Ferrara from the AA 2023/2024.

• Member of review group ("Gruppo di Riesame") for the three-year degree course in Agricultural technologies and sustainable management of agro-ecosystems (formerly Agricultural Technologies and Aquaculture of the Delta), Department of Chemical, Pharmaceutical and Agricultural Sciences, University of Ferrara, since A.Y. 2020/2021.

• Contact person for the TOLC-AV entrance skills test for the Agricultural technologies and sustainable management of agro-ecosystems course (formerly Agricultural Technologies and Aquaculture of the Delta) at the Department of Chemical, Pharmaceutical and Agricultural Sciences at the University of Ferrara, since A.Y. 2020/2021.

• Member of the Interest Group for Data Science in Food Safety Risk Assessment of the EFSA (European Food Safety Authority) for UNIFE. The technical group brings competencies in machine learning, natural language processing and data mining – from September 2021.

• Module 4 of Applicazioni dell’Intelligenza Artificiale in Medicina, Department of Translational Medicine and for Romagna in the A.Y. 2019/20 and 2023/2024.

• Deep Learning since A.Y. 2019/20 (MSc)

• Module Computer Science and Mathematics of the course Informatica, Matematica e Fisica since A.Y. 2020/21 (BSc)

• Co-Teacher of Fondamenti di Informatica e Laboratorio (Modulo B) in the A.Y. 2018/19 , 2019/20, 2023/2024, 2024/2025 (BSc)

• Project Work of Deep Learning since A.Y. 2023/2024 (MSc)

• Project Work of Computer Vision for A.Y. 2023/2024 (MSc)

• Co-teacher of Laboratorio di Intelligenza Artificiale since A.Y. 2023/2024 (MSc)

• Seminar “Introduction to Description Logics and the Semantic Web” for the course Fundamentals of Artificial Intelligence since A.Y. 2014/15 (MSc)