Teaching activities

Bachelor, master and PhD

• Algorithms for massive datasets @unimi master 2019-20
• Architectural partterns for distributed ML @unimi PhD 2019-20
• Big scale analytics @unimi master 2018-19
• Computer programming for data analysis @uca DUT 2019-20
• Computing education @unimi master 2018-19 – 2019-20
• Data bases II @uca DUT 2018-19
• Data mining @uca DUT 2018-19
• Statistics and data analytics @unimi bachelor 2018-19 – 2019-20

Other activities

• Algorithms for bioinformatics @unimi 2nd lev. specialization 2018-19
• Computer programming for bioinformatics @unimi 2nd lev. specialization 2018-19
• Data integration and visualization @unimi 2nd lev. specialization 2018-19

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
• 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
• Fostering a correct view of informatics PSR

Publications

[Malchiodi et al., 2020] Malchiodi D., da Costa Pereira C. and Tettamanzi A. G. B. Classifying Candidate Axioms via Dimensionality Reduction Techniques, in and V. Torra (Ed.), Proceedings of MDAI2020, Springer, Lecture Notes in Artificial Intelligence, 2020 [BIBTEX]

[Cermenati et al., 2020] Cermenati L., Malchiodi D. and Zanaboni A. Simultaneous Learning of Fuzzy Sets, in A. Esposito, M. Faundez-Zanuy, M. Morabito and E. Pasero (Eds.), Neural Approaches to Dynamics of Signal Exchanges, Singapore: Springer, Smart Innovation, Systems and Technologies, 167-175, 2020 [doi> BIBTEX]

[Lodi et al., 2019] Lodi M., Malchiodi D., Monga M., Morpurgo A. and Spieler B. Constructionist Attempts at Supporting the Learning of Computer Programming: A Survey, Olympiads in Informatics 13 (2019), 99—121 [doi> BIBTEX]

[Malchiodi and Zanaboni, 2019] Malchiodi D. and Zanaboni A. Data-Driven Induction of Shadowed Sets Based on Grade of Fuzziness, in R. Fullér, S. Giove and F. Masulli (Eds.), Fuzzy Logic and Applications — 12th International Workshop, WILF 2018 Genoa, Italy, September 6–7, 2018 — Revised Selected Papers, Cham: Springer Nature Switzerland AG, Lecture Notes in Artificial Intelligence 11291 (ISBN 978-3-030-12543-1/978-3-030-12544-8), 17—28, 2019 [doi> BIBTEX]

[Malchiodi et al., 2018] Malchiodi D., da Costa Pereira C. and Tettamanzi A. G. B. Predicting the Possibilistic Score of OWL Axioms through Support Vector Regression, in D. Ciucci, G. Pasi and B. Vantaggi (Eds.), Scalable Uncertainty Management. SUM 2018, Cham: Springer, Lecture Notes in Artificial Intelligence 11142 (ISBN 978-3-030-00460-6/978-3-030-00461-3), 2018 [doi> BIBTEX]

[Boldi et al., 2018] Boldi P., Frasca M. and Malchiodi D. Evaluating the impact of topological protein features on the negative examples selection, BMC Bioinformatics 19 - 14 (2018), 417.115–417.126 [doi> Open access link BIBTEX]

[Malchiodi and Tettamanzi, 2018] Malchiodi D. and Tettamanzi A. G. B. Predicting the Possibilistic Score of OWL Axioms through Modified Support Vector Clustering, in H. Haddad, R. L. Wainwright and R. Chbeir (Eds.), SAC'18: Proceedings of the 33rd Annual ACM Symposium on Applied Computing, ACM (ISBN 9781450351911), 1984–1991, 2018 [doi> BIBTEX]

[Malchiodi and Pedrycz, 2013] Malchiodi D. and Pedrycz W. Learning Membership Functions for Fuzzy Sets through Modified Support Vector Clustering, in F. Masulli, G. Pasi and R. Yager (Eds.), Fuzzy Logic and Applications. 10th International Workshop, WILF 2013, Genoa, Italy, November 19–22, 2013. Proceedings., Vol. 8256, Springer International Publishing, Switzerland, Lecture Notes on Artificial Intelligence (ISBN 978-3-319-03199-6), 52–59, 2013 [doi> BIBTEX]