Dario Fenoglio

Dario Fenoglio

PhD Student
Università della Svizzera italiana
Dario Fenoglio received his master’s degree in biomedical engineering from Politecnico di Torino in 2022. Since June 2023 he has joined the research group of Prof. Marc Langheinrich as a PhD student. His research focuses on the development of explainable machine-learning and deep-learning methods, combined with federated-learning techniques to ensure data privacy in healthcare.
Publications
Dario Fenoglio, Pasquale Polverino, Jacopo Quizi, Martin Gjoreski, Marc Langheinrich (2026). ERIS: Enhancing Privacy and Communication Efficiency in Serverless Federated Learning. CoRR.
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Dario Fenoglio, Arianna Casanova, Francesco De Santis, Mohan Li, Gabriele Dominici, Johannes Schneider, Martin Gjoreski, Marc Langheinrich, Pietro Barbiero, Giovanni de Felice (2026). Federated Concept-Based Models: Interpretable models with distributed supervision. CoRR.
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Dario Fenoglio, Daniil E. Kirilenko, Martin Gjoreski, Marc Langheinrich (2026). Federated Learning with Energy-Based Structured Probabilistic Inference. CoRR.
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Mohan Li, Dario Fenoglio, Martin Gjoreski, Marc Langheinrich (2026). Federated Learning with Profile Mapping under Distribution Shifts and Drifts. CoRR.
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Dario Fenoglio, Mohan Li, Pietro Barbiero, Nicholas D. Lane, Marc Langheinrich, Martin Gjoreski (2025). FLUX: Efficient Descriptor-Driven Clustered Federated Learning under Arbitrary Distribution Shifts. CoRR.
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Dario Fenoglio, Mohan Li, Davide Casnici, Matías Laporte, Shkurta Gashi, Silvia Santini, Martin Gjoreski, Marc Langheinrich (2025). Multi-Frequency Federated Learning for Human Activity Recognition Using Head-Worn Sensors. CoRR.
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Dario Fenoglio, Gabriele Dominici, Pietro Barbiero, Alberto Tonda, Martin Gjoreski, Marc Langheinrich (2024). Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning. Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, NeurIPS 2024, Vancouver, BC, Canada, December 10 - 15, 2024.
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Dario Fenoglio, Gabriele Dominici, Pietro Barbiero, Alberto Tonda, Martin Gjoreski, Marc Langheinrich (2024). Federated Behavioural Planes: Explaining the Evolution of Client Behaviour in Federated Learning. CoRR.
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Dario Fenoglio, Mohan Li, Davide Casnici, Matías Laporte, Shkurta Gashi, Silvia Santini, Martin Gjoreski, Marc Langheinrich (2024). Multi-Frequency Federated Learning for Human Activity Recognition Using Head-Worn Sensors. International Conference on Intelligent Environments, IE 2024, Ljubljana, Slovenia, June 17-20, 2024.
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Dario Fenoglio, Martin Gjoreski, Marc Langheinrich (2023). A Federated Unsupervised Personalisation for Cognitive Workload Estimation. Proceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia, MUM 2023, Vienna, Austria, December 3-6, 2023.
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Massimo Salvi, Claudia Manini, Jose I. López, Dario Fenoglio, Filippo Molinari (2023). Deep learning approach for accurate prostate cancer identification and stratification using combined immunostaining of cytokeratin, p63, and racemase. Comput. Medical Imaging Graph..
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Dario Fenoglio, Daniel Josifovski, Alessandro Gobbetti, Mattias Formo, Hristijan Gjoreski, Martin Gjoreski, Marc Langheinrich (2023). Federated Learning for Privacy-aware Cognitive Workload Estimation. Proceedings of the 22nd International Conference on Mobile and Ubiquitous Multimedia, MUM 2023, Vienna, Austria, December 3-6, 2023.
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