Teaching activities

Bachelor, master and PhD

• Algorithms for massive data (DSE) @unimi master 2023-24 – 2024-25
• Algorithms for massive datasets @unimi master 2023-24 – 2024-25
• Deep learning in bioinformatics @unimi PhD 2023-24
• Efficacy and efficiency evaluation of machine learning models @unimi PhD 2023-24
• Statistics and data analytics @unimi bachelor 2023-24 – 2024-25

Research

Research areas

• Data-driven induction of fuzzy sets
• Compression of machine learning models
• Mining of knowledge bases in semantic Web
• Negative example selection in bioinformatics
• ML-based COVID-19 risk prediction
• Application of ML in veterinary and forensics
• Popularization of informatics culture

Projects

• Multicriteria Data Structures and Algorithms: from compressed to learned indexes, and beyond PRIN

Publications

[Nicolini et al., 2025] Nicolini Marco, Emanuele, Jimenez Franco Ruben E., Cavalleri Emanuele, Galeano Alfonso Aldo J., Malchiodi Dario, Paccanaro Alberto, Robinson Peter N., Casiraghi Elena and Valentini Giorgio Fine-tuning of conditional Transformers improves in silico enzyme prediction and generalization, Computational and Structural Biotechnology Journal 27 (2025), 1318–1334 [doi> BIBTEX]

[Biagiotti et al., 2025] Biagiotti Alessandro, Malchiodi Dario, Mariotto Samuele and Rossi Lucio Quench detection and localization via interpretable machine learning, in L. Iliadis, I. Maglogiannis, E. Kyriacou and C. Jayne (Eds.), Engineering Applications of Neural Networks. EANN 2025., Vol. 2582, Cham: Springer, Communications in Computer and Information Science, 151–164, 2025 [doi> BIBTEX]

[Malchiodi et al., 2025] Malchiodi Dario, Zanaboni Anna M., Di Gioacchino Alessandro and Bonizzoni Letizia One-class vs binary machine learning classification of ceramic samples described by chemical element concentrations, Journal of Cultural Heritage 71 (2025), 234–241 [doi> BIBTEX]

[Cavalleri et al., 2024] Cavalleri Emanuele, Soto-Gomez Mauricio, Pashaeibarough Ali, Malchiodi Dario, Caufield Harry, Reese Justin, Mungall Christopher J., Robinson Peter N., Casiraghi Elena, Valentini Giorgio and Mesiti Marco Initial achievements in relation extraction from RNA-focused scientific papers, in M. Atzori, P. Ciacca, M. Ceci, F. Mandreoli, D. Malerba, M. Sanguinetti, A. Pellicani and F. Motta (Eds.), Proceedings of the 32nd Symposium on Advanced Database Systems, 61–69, 2024 [BIBTEX]

[Paravisi et al., 2024] Paravisi Mattia, Visconti Andrea and Malchiodi Dario Security Analysis of Cryptographic Algorithms: Hints from Machine Learning, in L. Iliadis, I. Maglogiannis, A. Papaleonidas, E. Pimenidis and C. Jayne (Eds.), Engineering Applications of Neural Networks. EANN 2024., Vol. 2141, Cham: Springer, Communications in Computer and Information Science, 569–580, 2024 [doi> BIBTEX]

[Frasson and Malchiodi, 2024] Frasson Marco and Malchiodi Dario Support Vector Based Anomaly Detection in Federated Learning, in L. Iliadis, I. Maglogiannis, A. Papaleonidas, E. Pimenidis and C. Jayne (Eds.), Engineering Applications of Neural Networks. EANN 2024., Vol. 2141, Cham: Springer, Communications in Computer and Information Science, 274–287, 2024 [doi> BIBTEX]

[Malchiodi et al., 2024] Malchiodi Dario, Raimondi Davide, Fumagalli Giacomo, Giancarlo Raffaele and Frasca Marco The role of classifiers and data complexity in learned Bloom filters: insights and recommendations, Journal of Big Data 11 - 45 (2024) [doi> BIBTEX]

[Cavalleri et al., 2024a] Cavalleri Emanuele, Soto-Gomez Mauricio, Pashaeibarough Ali, Malchiodi Dario, Caufield Harry, Reese Justin, Mungall Christopher J., Robinson Peter N., Casiraghi Elena, Valentini Giorgio and Mesiti Marco SPIREX: Improving LLM-based relation extraction from RNA-focused scientific literature using graph machine learning , in Proceedings of Workshops at the 50th International Conference on Very Large Data Bases, vldb.org, 1–11, 2024 [BIBTEX]

[Nicolini et al., 2024] Nicolini Marco, Malchiodi Dario, Cabri Alberto, Cavalleri Emanuele, Mesiti Marco, Paccanaro Alberto, Robinson Peter N., Reese Justin, Casiraghi Elena and Valentini Giorgio Fine-Tuning of Conditional Transformers Improves the Generalization of Functionally Characterized Proteins, in BIOSTEC 2024 - 17th International Joint Conference on Biomedical Engineering Systems and Technologies - Proceedings, Vol. 1, SCITEPRESS (ISBN 978-989-758-688-0), 561–568, 2024 [doi> BIBTEX]

[Gliozzo et al., 2024] Gliozzo Jessica, Marinò Giosuè, Bonometti Arturo, Frasca Marco and Malchiodi Dario Resource-Limited Automated Ki67 Index Estimation in Breast Cancer, in Proceedings of the 2023 10th International Conference on Bioinformatics Research and Applications (ICBRA '23), New York, NY, USA: ACM, 165–172, 2024 [doi> BIBTEX]

[Valentini et al., 2023] Valentini Giorgio, Malchiodi Dario, Gliozzo Jessica, Mesiti Marco, Soto-Gomez Mauricio, Cabri Alberto, Reese Justin, Casiraghi Elena and Robinson Peter N. The promises of large language models for protein design and modeling, Frontiers in Bioinformatics 3 (2023), 1304099.1—1304099.11 [doi> BIBTEX]

[Marinò et al., 2023] Marinò Giosuè C., Furia Flavio, Malchiodi Dario and Frasca Marco Efficient and Compact Representations of Deep Neural Networks via Entropy Coding, IEEE Access 11 (2023), 106103—106125 [doi> BIBTEX]

[Ruschioni et al., 2023] Ruschioni Giulia, Malchiodi Dario, Zanaboni Anna M. and Bonizzoni Letizia Supervised learning algorithms as a tool for archaeology: classification of ceramic samples described by chemical element concentrations, Journal of Archaeological Science: Reports 49 (2023), 103995 [doi> BIBTEX]

[Malchiodi et al., 2023] Malchiodi Dario, Raimondi Davide, Fumagalli Giacomo, Giancarlo Raffaele and Frasca Marco A Critical Analysis of Classifier Selection in Learned Bloom Filters: the Essentials, in L. Iliadis, I. Maglogiannis, S. Alonso Castro, C. Jayne and E. Pimenidis (Eds.), Engineering Application of Neural Networks — 24th International Conference — EAAAI/EANN 2023 — León, Spain, June 14—17, 2023 —Proceedings, Springer Nature, Communications in Computer and Information Science 1826, 47–61, 2023 [doi> preprint BIBTEX]

[Marinò et al., 2023a] Marinò Giosuè C., Petrini Alessandro, Malchiodi Dario and Frasca Marco Deep neural networks compression: a comparative survey and choice recommendations, Neurocomputing 520 (2023), 152–170 [doi> BIBTEX]

[Condorelli and Malchiodi, 2022] Condorelli Andrea and Malchiodi Dario Designing a Master Course on Architectures for Big Data: A Collaboration Between University and Industry, Informatics in Education 4 (2022), 635–653 [doi> BIBTEX]

[Zanaboni et al., 2022] Zanaboni Anna M., Malchiodi Dario, Bonizzoni Letizia and Ruschioni Giulia Classification of Pottery Fragments Described by Concentration of Chemical Elements, in P. L. Mazzeo, E. Frontoni, S. Sclaroff and C. Distante (Eds.), Image Analysis and Processing. ICIAP 2022 Workshops. ICIAP 2022., Vol. 13373, Cham: Springer, Lecture Notes in Computer Science (ISBN 978-3-031-13320-6), 141–151, 2022 [doi> BIBTEX]

[Fumagalli et al., 2022] Fumagalli Giacomo, Raimondi Davide, Giancarlo Raffaele, Malchiodi Dario and Frasca Marco On the Choice of General Purpose Classifiers in Learned Bloom Filters: An Initial Analysis Within Basic Filters, in Proceedings of the 11th International Conference on Pattern Recognition Applications and Methods — ICPRAM, SciTePress (ISBN 978-989-758-549-4), 675–682, 2022 [doi> BIBTEX]

[Galizzi et al., 2021] Galizzi Alberto, Bagardi Mara, Stranieri Angelica, Zanaboni Anna M., Malchiodi Dario, Borromeo Vitaliano, Brambilla Paola G. and Locatelli Chiara Factors affecting the urinary aldosterone-to-creatinine ratio in healthy dogs and dogs with naturally occurring myxomatous mitral valve disease, BMC Veterinary Research 17 - 1 (2021), 1–14 [doi> BIBTEX]