Professor Fabio Antonio Stella

Prof. Fabio Stella

Director

Fabio Stella, PhD in Computational Mathematics and Operations Research, is a Full Professor of Operation Research at the Department of Informatics, Systems and Communication of the University of Milano-Bicocca. His main research interests are rooted in artificial intelligence (AI) and Machine Learning (ML), with specific reference to Bayesian causal networks. Fabio published more than 100 papers and served as Program Chair/Reviewer of the following top international conferences on AI and ML; AISTATS, ICLR, ICML, IJCAI, PGM, NeurIPS, PAKDD, RecSys, SIGIR, ECAI, and UAI. He has been awarded as 10% best reviewer at NeurIPS in 2020, 2022, 2023, at ICML and AISTATS in 2022 and at IJCAI in 2023. He is Area Chair at NeurIPS 2024, since 2021 serves as Associate Editor of IEEE Intelligent Systems, and since 2024 serves as Action Editor for Transactions on Machine Learning Research. Fabio is currently leading as Principal Investigator two international research projects, funded on the basis of a competitive procedure by the European Commission.

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Alessandro Bregoli

 

Alessandro Bregoli

Post-Doc

Ph.D. in computer science focusing on machine learning at the University of Milan-Bicocca. During his thesis for his bachelor’s degree, he worked on topic models. During the master’s degree, he focused on anomaly detection on multidimensional time series. In the last four years, he studied the probabilistic graphical models from the theoretical and application points of view. Specifically, he worked with influence diagrams, dynamic Bayesian networks and continuous-time Bayesian networks.

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Alessio Zanga

 

Alessio Zanga

PhD Candidate

Ph.D. candidate at the University of Milano-Bicocca, fully funded by F. Hoffman – La Roche Ltd. My Ph.D. project is about Causal Discovery applied to Healthcare and Medicine, in particular in the context of risk assessments of lymph node metastases in Endometrial Cancer patients. In recent years, I also covered different positions, such as adjunct professor for the master course of Causal Networks, research consultant for the Max Planck Institute and training consultant for Fondazione Aldini Valeriani. Additionally, I’m also on the Program Committee of the Workshop for Healthcare of the Italian Association of Artificial Intelligence.

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Alice Bernasconi

 

Alice Bernasconi

PhD Candidate

Researcher in Epidemiology at Fondazione IRCCS Istituto Nazionale dei Tumori, Milano, since 2017. My main research area is cancer in Adolescents and Young Adults and its late sequelae. In 2021 I started a Ph.D. program at the Department of Computer Science of the University of Milano-Bicocca: my Ph.D. project focuses on Cardiovascular Risk Prediction in young Breast Cancer Survivors.

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Emanuele Cavenaghi

 

Emanuele Cavenaghi

PhD Candidate

Ph.D. candidate in the Faculty of Engineering at the Free University of Bozen-Bolzano. My research is focused on applying Causality in the Recommended Systems domain. Particularly, I’m working to bridge the Structural Causal Model and Potential Outcomes frameworks to Recommender Systems and apply them in concrete cases to Online Hotel Recommendation through collaboration with web companies.

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Marco Locatelli

 

Marco Locatelli

PhD Candidate

Ph.D. candidate, funded by the European Union, in the Department of Computer Science of the University of Milano-Bicocca. My research focuses on Bayesian Causal Networks applied to personalized medicine. In particular, my project concentrates on the development of a clinical decision support tool to guide the selection of the best patient-centered treatment for Myasthenia Gravis (MG) disease.

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Niccolò Rocchi

 

Niccolò Rocchi

PhD Candidate

Ph.D. candidate funded by “Fondazione IRCCS Istituto Nazionale dei Tumori di Milano (INT)” and the University of Milano-Bicocca linked to the research project: “Causal models for prediction and decision making from multiple data sources”. The project focuses on Causal Discovery when multiple sources, partially overlapping or private, are needed to infer causal relationships in various cohorts. The major real-world application is the one of rare cancers. I’m actively taking part in the IDEA4RC European project, and I held the position of adjunct professor for the Causal Networks Master’s Degree course.

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Federico Pirola

 

Federico Pirola

PhD Candidate

First-year Ph.D. candidate in Computer Science from the University of Milano-Bicocca with a background in Statistics and Data Science. I’m funded by ANTHEM and my project for the next three years will focus on the implementation of causal methods and models to identify causal-effect relationships in the context of neurodegenerative diseases. Specifically, the project aims to recognize biomarkers and biomolecules responsible for the development and progression of Parkinson’s disease.

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Justin Armanini

PhD Candidate

Ph.D. in Computer Science at the University of Milano-Bicocca, funded by “Fondazione IRCCS Istituto Nazionale dei Tumori di Milano (INT)”. My Ph.D. project focuses on Causal Natural Language Processing, an emerging research area that extends causality’s applicability to natural language data. Concretely, I am working to develop causal models starting from textual data within the healthcare domain.

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Francesco Canonaco

 

Francesco Canonaco

PhD Candidate

Ph.D. candidate, funded by Minutia.AI, in the Department of Computer Science of the University of Milano-Bicocca. My research focuses on the Bayesian Network framework and its applications for investigating the mechanisms of the human microbiome and its impact on health.

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Academic Collaborations

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