Dario Malchiodi
Associate Professor
PhD: 2000; PhD in Computational Mathematics and Operations Research; University of Milan
MSc: 1997; MSc in Computer Science; University of Milano
Email: dario (dot) malchiodi (at) unimi (dot) it
Main interests: machine learning, fuzzy set induction, data quality in machine learning
Dario Malchiodi is currently associate professor at the Department of Computer Science, University of Milan, member of scientific board of the Data science research center at the University of Milan, visiting professor at the Université de la Côte d'Azur, France, and visiting scientist at INRIA, France. His research activities fall in the area of machine learning, with particular interest in fuzzy set induction and data quality issues. He is author of around 100 scientific publications with peer-review in journals, book chapters and international conferences in the field of Machine Learning.
Publications
M. Mesiti, M. Notaro, D. Malchiodi and M. Andrade-Navarro. Disease--Genes Must Guide Data Source Integration in the Gene Prioritization Process. Computational Intelligence Methods for Bioinformatics and Biostatistics: 14th International Meeting, CIBB 2017, Cagliari, Italy, September 7-9, 2017, Revised Selected Papers 10834, 2019.
M. Frasca and D. Malchiodi. Exploiting negative sample selection for prioritizing candidate disease genes. Genomics and Computational Biology 3(3), 2017.
M. Frasca and D. Malchiodi. Selection of Negatives in Hopfield Networks. International Workshop on Dynamics of Multi-Level Systems (DYMULT), 2015.
P. Boldi, M. Frasca and D. Malchiodi. Evaluating the impact of topological protein features on the negative examples selection. BMC Bioinformatics, BioMed Central 19(14), 2018.
M. Frasca, F. Lipreri and D. Malchiodi. Analysis of informative features for negative selection in protein function prediction. International Conference on Bioinformatics and Biomedical Engineering, 2017.
M. Frasca, J. Fontaine, G. Valentini, M. Mesiti, M. Notaro, D. Malchiodi and M. Andrade-Navarro. Disease--Genes must Guide Data Source Integration in the Gene Prioritization Process. International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, 2017.