Dario Malchiodi

Università degli Studi di Milano unimi
(associate professor)
INRIA + UCA INRIA + UCA
(visiting scientist)
Université de la Côte d'Azur uca
(visiting professor)
Data Science Research Centre DSRC
(scientific board)

first . last at unimi . it

PGP 470D 8811 C4B3 787A

dariomalchiodi

@dariomalchiodi

Dario Malchiodi

0000-0002-7574-697X

Scopus ID: 6507119064

Dario_Malchiodi

@dariomalchiodi

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Information
01/04/2020 Lab lectures for the Statistics and data analytics course The optional lab for the Statistics and data analysis course will start on Friday, April 3rd, via distance learning. Students can download the dataset which will be analyzed during the first lecture, as well as its description.
17/03/2020 Movement of video lectures In a few days, the recordings of the lectures will be moved to the University's OneDrive space. Students are therefore invited to check that their academic account linked to Office365 is activated.
12/03/2020 Remote office hours organization Starting today, office hours will take place remotely. On each Thursday, students can connect from 17:00 to the meeting «ricevimento-malchiodi» organized on meet.jit.si , writing their name and surname in the chat, and waiting to be called. The channel is open to all participants, so the need for private office hours must be reported, always in the chat, when connecting.
06/03/2020 Organization of distance learning Until further notice, the lectures of «Statistics and data analysis» and «Algorithms for massive datasets» will take place via distance learning. On the days when a course is scheduled, a video recording of the lesson will be made available on the corresponding Web page. Students can send questions to the teacher via email on any clarifications: the following day a documentcontaining the answer to the questions of general interest will be published.

Teaching activities

Bachelor, master and PhD

Algorithms for massive datasets @unimi master 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
Architectural partterns for distributed ML @unimi PhD 2019-20
Computer programming for bioinformatics @unimi 2nd lev. specialization 2018-19
Data integration and visualization @unimi 2nd lev. specialization 2018-19

All activities

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

All areas

Projects

Multicriteria Data Structures and Algorithms: from compressed to learned indexes, and beyond PRIN
Fostering a correct view of informatics PSR

All projects

Publications

[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]

All publications