Dario Malchiodi
Università degli Studi di Milano unimi
(associate professor)
INRIA + UCA INRIA + UCA
(visiting scientist)
Data Science Research Centre DSRC
(scientific board)
first . last at unimi . it
Dario Malchiodi| News |
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26/03/2025 teaching AMD Classroom change for the AMD lectures Starting April 1st, the tuesday lectures of the «Algorithms for massive datasets» course will take place in the «Laboratorio magistrale» classroom on the 3rd floor of the Computer Science Department. The wednesday lectures will take place in the same classroom, starting April 9th. The time schedule will remain unchanged. |
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26/03/2025 research Accepted paper in «Computational and Structural Biotechnology» The paper «Fine-tuning of conditional transformers improves in silico enzyme prediction and generation», which I coauthored with M. Nicolini, E. Saitto, R. E. Jimenez Franco, E. Cavalleri, A. J. Galeano Alfonso, A. Paccanaro, P. N. Robinson, E. Casiraghi and G. Valentini, has been accepted for publication in Computational and Structural Biotechnology Journal. |
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25/03/2025 research Accepted paper at the EAAAI 2025 Conference The paper «Quench detection and localization via interpretable machine learning», wich I coauthored with A. Biagiotti, S. Mariotto and L. Rossi, has been accepted for presentation at the EAAAI 2025 Conference. |
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20/03/2025 teaching AMD Classroom change for the AMD lectures Starting April 1st, the lectures of the course «Algorithms for massive datasets» will take place in the «Laboratorio magistrale» classroom on the 3rd floor of the Computer Science Department. |
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
All projectsPublications
[Nicolini et al., 2025] Fine-tuning of conditional Transformers improves in silico enzyme prediction and generalization, Computational and Structural Biotechnology Journal 27 (2025), 1318-1334 [doi> ]
[Biagiotti et al., 2025] Quench detection and localization via interpretable machine learning, in L. Iliadis, I. Maglogiannis, E. Kyriacou and C. Jayne (Eds.), Proceedings of the 26th Engineering Applications of Neural Networks Conference – EANN/EAAAI 2025., Cham: Springer, 2025, In press []
[Malchiodi et al., 2025] One-class vs binary machine learning classification of ceramic samples described by chemical element concentrations, Journal of Cultural Heritage 71 (2025), 234-241 [doi> ]
[Paravisi et al., 2024] 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> ]
[Frasson and Malchiodi, 2024] 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> ]
[Malchiodi et al., 2024] The role of classifiers and data complexity in learned Bloom filters: insights and recommendations, Journal of Big Data 11 - 45 (2024) [doi> ]
[Cavalleri et al., 2024] 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 []
[Nicolini et al., 2024] 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> ]
[Gliozzo et al., 2024] 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> ]
[Valentini et al., 2023] The promises of large language models for protein design and modeling, Frontiers in Bioinformatics 3 (2023), 1304099 [doi> ]
[Marinò et al., 2023] Efficient and Compact Representations of Deep Neural Networks via Entropy Coding, IEEE Access 11 (2023), 106103—106125 [doi> ]
[Ruschioni et al., 2023] 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> ]
[Malchiodi et al., 2023] 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 ]
[Marinò et al., 2023a] Deep neural networks compression: a comparative survey and choice recommendations, Neurocomputing 520 (2023), 152—170 [doi> ]
[Condorelli and Malchiodi, 2022] Designing a Master Course on Architectures for Big Data: A Collaboration Between University and Industry, Informatics in Education 4 (2022), 635—653 [doi> ]
[Zanaboni et al., 2022] 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> ]
[Fumagalli et al., 2022] 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> ]
[Galizzi et al., 2021] 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> ]
All publications