Prof. Elena Bellodi

Associate Professor

Department of Engineering, University of Ferrara


Coordinator

Statistical Relational AI Lab

Department of Engineering, University of Ferrara

Corpo A, Polo Scientifico Tecnologico

Via Saragat 1, 44122, Ferrara, Italy

Tel/Fax: +39 0532 974882 

Email: elena.bellodi@unife.it 

University webpage

Short Bio

Elena Bellodi is Associate Professor in the Department of Engineering of the University of Ferrara, where she graduated in Computer and Automation Engineering and obtained her PhD in Engineering Sciences. She is part of the AI@UniFE group since 2009. Her research interests include Machine Learning, Probabilistic Logic Programming and Statistical Relational Artificial Intelligence, Description Logics and the Semantic Web, Process Mining, Natural Language Processing.

She is the author of more than 90 works, including conference papers, international journals, and book chapters. 

Awards

For a complete list of publications see: 

Research Project Coordination

AIR | Advanced Integrated machine leaRning, 2024-2025



PRODE | PRObabilistic DEclarative Process Mining, 2023-2025



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


The project is expected to optimize sustainable mobility solutions, reduce emissions, and foster a regional data-sharing infrastructure, providing actionable insights for businesses, policymakers, and the public to promote eco-friendly tourism and urban mobility across Emilia-Romagna. The main technologies on which the project is based are Artificial Intelligence, Machine learning, Big data, Internet of Things.

Research Experience

Dinamiche di opinioni e intelligenza artificiale

Opinion Dynamics and Artificial Intelligence

Bando FIRD (“FONDO INTERDISCIPLINARE PER LA RICERCA DIPARTIMENTALE”) 2023, financed by University of Ferrara. Participant. This project aims to apply machine learning techniques, particularly natural language processing, to improve and develop mathematical models that better reflect social dynamics. Specifically, by objectively quantifying opinion, we expect to gain a deeper understanding of dynamics on social networks, from the spread of fake news to the presence of polarization, echo chambers, and their related effects.

Sviluppo e validazione di una nuova formula basata sull’intelligenza artificiale per il calcolo del potere delle lente intraoculare impiantata durante l’intervento di cataratta

Development and validation of a new artificial intelligence-based formula for calculating the power of the intraocular lens implanted during cataract surgery

Bando 5x1000 2022, financed by University of Ferrara. Participant. This project aimed to develop a new formula for calculating IOL (intraocular lens) using machine learning techniques, with the objective of improving the accuracy and precision of refractive outcomes in cataract surgery. The formula will be built and tested on a sample of normal eyes as well as eyes with other comorbidities or those that have undergone previous combined surgeries. The performance of the new formula will be compared with the results obtained using other traditional formulas. 

No esitazione (NOE'). Per una comunicazione efficace della vaccinazione anti covid-19

No Hesitation (NOE’): For effective communication of the Covid-19 vaccination

Bando FIR (“FONDO PER L’INCENTIVAZIONE ALLA RICERCA”) 2021, financed by University of Ferrara. Participant. The aim of the NOE’ project was to develop a communication strategy targeting the segment of the Italian population that is resistant to getting vaccinated against the SARS-CoV-2 virus, which is responsible for the current Covid-19 pandemic. To achieve this goal, the project employed an innovative and multidisciplinary methodology, involving close interaction between communication and social research methods, data science approaches, and mathematical modeling techniques. See the following publications: PLOS ONE, NL4AI 2022, MEDIASCAPES JOURNAL

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.


GST4Water | Green Smart Technology for Water, 2016-2018


Green Smart Technology for Water (GST4Water), 2016-2018, financed by Regione Emilia-Romagna (POR-FESR2014-20). Participant. 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

Decision Support System to improve appropriateness of repeated execution of laboratory examinations, 2012-2015


Decision Support System to improve appropriateness of repeated execution of laboratory examinations (2012-2015), financed by the Italian Ministry of Health under the “Ricerca Finalizzata 2010” call. Participant. See the following publications: ICHI2014, ICTAI2015, BMC Medical Informatics and Decision Making Journal

Editorial and Organizational Activities

Invited Talks

Service

Teaching