Areas of research

Our areas of research

Our group is actively engaged in investigating novel methodologies, developing innovative solutions, and addressing pressing challenges across a diverse range of research areas. Explore below to learn more about our current focus areas and ongoing projects.

Explainable Artificial Intelligence (XAI)

Methods:

  • Artificial Intelligence and Machine Learning
  • Explainability
  • Explainability of CNNs
  • Explainability of tabular data
  • Human-in-the-loop Explainability

Members:

  • A. Tocchetti
  • A. De Santis
  • M. Bianchi
  • R. Campi
  • M. Brambilla

Publications:

  • M Bianchi, A De Santis, A Tocchetti, M Brambilla, 2024, Interpretable Network Visualizations: A Human-in-the-Loop Approach for Post-hoc Explainability of CNN-based Image Classification, Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence. Main Track. Pages 3715-3723. https://doi.org/10.24963/ijcai.2024/411.
  • A Tocchetti, M Brambilla, 2022, The role of human knowledge in explainable AI, Data 7 (7), 93.
  • A Tocchetti, L Corti, A Balayn, M Yurrita, P Lippmann, M Brambilla, J Yang, 2022, AI robustness: a human-centered perspective on technological challenges and opportunities, arXiv preprint arXiv:2210.08906.
  • A Tocchetti, L Corti, M Brambilla, I Celino, 2022, EXP-crowd: a gamified crowdsourcing framework for explainability, Frontiers in Artificial Intelligence 5, 826499.

Computational Social Science (from cyber social threats to generative AI)

Methods:

  • Data Mining and Machine Learning
  • NLP

Members:

  • F. Corso
  • F. Pierri
  • M. Brambilla
  • S. Ceri

Publications:

  • F Pierri, B Perry, MR DeVerna, KC Yang, A Flammini, F Menczer, 2022, Online misinformation is linked to early COVID-19 vaccination hesitancy and refusal, Scientific Reports.
  • F Pierri, S Ceri, 2019, False news on social media: a data-driven survey, ACM Sigmod Record 48 (2), 18-27.
  • F Pierri, A Artoni, S Ceri, 2020, Investigating Italian disinformation spreading on Twitter in the context of 2019 European elections, PloS one 15 (1), e0227821.
  • F Pierri, C Piccardi, S Ceri, 2020, Topology comparison of Twitter diffusion networks effectively reveals misleading information, Scientific reports 10 (1), 1372.
  • F Pierri, L Luceri, N Jindal, E Ferrara, 2023, Propaganda and Misinformation on Facebook and Twitter during the Russian Invasion of Ukraine, WebSci’23 – 15th ACM Web Science Conference.
  • G Brena, M Brambilla, S Ceri, M Di Giovanni, F Pierri, G Ramponi, 2019, News sharing user behaviour on twitter: A comprehensive data collection of news articles and social interactions, Proceedings of the International AAAI Conference on Web and Social Media.
  • F Pierri, A Tocchetti, L Corti, MD Giovanni, S Pavanetto, M Brambilla, S Ceri, 2021, VaccinItaly: monitoring Italian conversations around vaccines on Twitter and Facebook, Workshop Proceedings of the 15th International AAAI Conference on Web and Social Media.
  • M Di Giovanni, F Pierri, C Torres-Lugo, M Brambilla, 2022, VaccinEU: COVID-19 vaccine conversations on Twitter in French, German and Italian, Proceedings of the AAAI international conference on web and social media (ICWSM) 2022.
  • M Di Giovanni, L Corti, S Pavanetto, F Pierri, A Tocchetti, M Brambilla, 2021, A Content-based Approach for the Analysis and Classification of Vaccine-related Stances on Twitter: the Italian Scenario, Workshop Proceedings of the 15th International AAAI Conference on Web and Social Media.
  • F Pierri, 2023, Political advertisement on Facebook and Instagram in the run up to 2022 Italian general election, WebSci’23 – 15th ACM Web Science Conference.
  • F Pierri, G Liu, S Ceri, 2023, ITA-ELECTION-2022: A multi-platform dataset of social media conversations around the 2022 Italian general election, CIKM ’23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management.
  • Bär, D., Pierri, F., Morales, G.D.F. and Feuerriegel, S., 2023. Auditing targeted political advertising on social media during the 2021 German election. arXiv preprint arXiv:2310.10001.

Viral genomic surveillance for public health

Methods:

  • Conceptual Modeling
  • Database Management Systems (DBMS)
  • Data Mining and Machine Learning

Keywords:

  • Virology
  • Genomic annotation
  • Visualization

Members:

  • T. Alfonsi
  • A. Bernasconi
  • S. Ceri
  • P. Pinoli

Collaborators:

Publications:

  • Pinoli, P., Canakoglu, A., Ceri, S., Chiara, M., Ferrandi, E., Minotti, L. and Bernasconi, A., 2023. VariantHunter: a method and tool for fast detection of emerging SARS-CoV-2 variants. Database, 2023, p.baad044.
  • Alfonsi, T., Bernasconi, A., Chiara, M. and Ceri, S., 2023. Data-driven recombination detection in viral genomes. Nature Communications 15, 3313.
  • Al Khalaf, R., Bernasconi, A., Pinoli, P. Impact of Omicron subvariants’ mutations on B cell and T cell epitopes: A systematic data analysis. [Accepted for publication in Plos ONE]

FAIRification of scientific datasets

Methods:

  • Conceptual Modeling
  • Database Management Systems (DBMS)

Keywords:

  • Ontologies
  • Controlled Vocabulary
  • Interoperability Resources

Members:

  • N. Barret
  • A. Bernasconi
  • B. Bikbov
  • P. Pinoli

Collaborators:

Publications:

  • Bernasconi, A., Simon, A.G., Guizzardi, G., Bonino, L.O. and Storey, V.C., 2023, June. Ontological representation of FAIR principles: A blueprint for FAIRer data sources. In International Conference on Advanced Information Systems Engineering (pp. 261-277). Cham: Springer Nature Switzerland.
  • Bernasconi, A., Cappiello, C., Ceri, S. and Pinoli, P., 2024. Achieving data FAIRification in a distributed analytics research platform for rare diseases. In 15th International Conference on Semantic Web Appplications and Tools for Health Care and Life Sciences.

Topic modeling architectures for user-centered domain exploration

Methods:

  • ​​Database Management Systems (DBMS)
  • Natural Language Processing (NLP)
  • Data Mining and Machine Learning
  • Human-computer Interaction

Keywords:

  • Dynamic Topic modeling
  • LLMs
  • Science of science
  • Web data
  • Time series

Members:

  • A. Bernasconi
  • F. Invernici
  • S. Ceri

Collaborators:

Publications:

  • Invernici, F., Bernasconi, A. and Ceri, S. Exploring the evolution of research topics during the COVID-19 pandemic. (2024) Expert Systems with Applications 252, 124028.

Grounding Systemic Design with Data Science Methods

Methods:

  • Conceptual Modeling
  • Database Management Systems (DBMS)

Keywords:

  • Systemic Design
  • Causal Loop Diagrams
  • Repository
  • Reinforcing dynamics

Members:

  • A. Bernasconi
  • S. Ceri

Collaborators:

  • C. Leonardi (independent researcher, Systemic Designer)

Reactive Graph-based knowledge management

Methods:

  • Conceptual Modeling
  • Database Management Systems (DBMS)
  • Data Mining

Keywords:

  • Neo4j
  • graph databases
  • association rules mining
  • triggers
  • reactive systems

Members:

  • A. Bernasconi
  • F. Cambria
  • S. Ceri
  • F. Invernici
  • D. Magnanimi

Collaborators:

  • L. Mari (PoliMi)

Publications:

  • Ceri, S., Bernasconi, A., Gagliardi, A. Reactive Knowledge Management. 2024 IEEE 40th International Conference on Data Engineering (ICDE), Utrecht, Netherlands, 2024 pp. 5574-5582.
  • Ceri, S., Bernasconi, A., Gagliardi, A., Martinenghi, D., Bellomarini, L., Magnanimi, D. PG-Triggers: Triggers for Property Graphs. SIGMOD/PODS ’24: Companion of the 2024 International Conference on Management of Data. June 2024 Pages 373–385.
  • Invernici, F., Bernasconi, A., Ceri, S., Searching COVID-19 Clinical Research Using Graph Queries: Algorithm Development and Validation. (2024) Journal of Medical Internet Research 26, e52655.
  • Bellomarini, L., Bernasconi, A., Ceri, S., Gagliardi, A., Magnanimi, D., Martinenghi, D. Towards a Standard for Triggers in Property Graphs. Proceedings of the 32nd Symposium on Advanced Database Systems. (Vol. 3741). CEUR-WS.