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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)


Information
24/01/2020
Public correction of the Statistics and data analysis written test of Januery, 20th 2020
The public correction of the written test of Statistics and data analysis of 20/1/20 will take place at 10:00 on 4/2 in Lab. Laurea Magistrale 3rd floor. Students with further questions will be able to view their own test.
24/01/2020
Results of the Statistics and data analysis written test of January, 20th 2020 and oral test calendar
Students enrolled in the Statistics and data analytics test of 20/1 should receive an e-mail message showing their result. The oral tests will take place in the computer science department, according to the following schedule organized by last name initial: 28/1 9:30 sala riunioni 4° piano (A to CA), 29/1 14:30 lab. magistrale 5° piano (CE to F), 30/1 9:30 lab. magistrale 5° piano (G to M), 31/1 9:30 lab. magistrale 5° piano (N to Z).
21/01/2020
Beginning of the Algorithms for massive datasets course
The lectures of Algorithms for massive datasets will start on Wednesday February, 26th at 14:30 in classroom alfa of the Computer science department.
14/01/2020
Place and time of the Statistics and data analysis written test of January 20th, 2020
The Statistics and data analytics written test of 20/1 will take place in the classrooms at the first floor of the Computer science department, starting from 13:30. Participants may bring a book and a notebook with them for consultation.

Teaching activities


Bachelor, master and PhD

  • Algorithms for massive datasets @unimi master Lectures are in English 2019-20
  • Big scale analytics @unimi master Lectures are in italian 2018-19
  • Computer programming for data analysis @uca DUT Lectures are in french 2019-20
  • Computing education @unimi master Lectures are in italian 2018-192019-20
  • Data bases II @uca DUT Lectures are in french 2018-19
  • Data mining @uca DUT Lectures are in french 2018-19
  • Statistics and data analytics @unimi bachelor Lectures are in italian 2018-192019-20

Other activities

  • Algorithms for bioinformatics @unimi 2nd lev. specialization Lectures are in English 2018-19
  • Architectural partterns for distributed ML @unimi PhD Lectures are in English 2019-20
  • Computer programming for bioinformatics @unimi 2nd lev. specialization Lectures are in English 2018-19
  • Data integration and visualization @unimi 2nd lev. specialization Lectures are in English 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

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