FERRARI DACREMA MAURIZIO
Research assistant
Research collaborator
Research collaborator
Personal Page:
https://mauriziofd.github.io/
https://mauriziofd.github.io/
Maurizio Ferrari Dacrema is a postdoctoral researcher at the Dipartimento di Elettronica, Informazione e Bioingegneria (DEIB) of Politecnico di Milano.
In 2020 he received a PhD Cum Laude in Information Technology from Politecnico di Milano, with a thesis titled “An assessment of reproducibility and methodological issues in neural recommender systems research”. In 2019 he was awarded the Best ACM Long Paper Award for the paper “Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches”. His main research interests are recommender systems, with particular focus on the independent evaluation and reproducibility of published research, as well as the application of currently available Quantum Computing technology for optimization and machine learning tasks.
Since 2014 he worked as lab tutor and teaching assistant for various courses at Bachelor and Master level. In 2020 he was lecturer for the PhD course “Applied Quantum Machine Learning”. Since 2014 he has worked as an expert in quality assurance of higher education institutions and was involved in several accreditation visits for the National Agency for the Evaluation of the University system and Research (ANVUR) and for the QUACING agency for EUR-ACE accreditation of engineering courses. He was also involved in some international evaluations of european universities for Horizon2020 and Erasmus+ projects with the agencies NVAO and AQU Catalunya. He is a member of the international experts register of the agencies AIKA and THEQC. From 2011 to 2014 he was a member of various university’s commissions involved in quality assurance processes.
In 2020 he received a PhD Cum Laude in Information Technology from Politecnico di Milano, with a thesis titled “An assessment of reproducibility and methodological issues in neural recommender systems research”. In 2019 he was awarded the Best ACM Long Paper Award for the paper “Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches”. His main research interests are recommender systems, with particular focus on the independent evaluation and reproducibility of published research, as well as the application of currently available Quantum Computing technology for optimization and machine learning tasks.
Since 2014 he worked as lab tutor and teaching assistant for various courses at Bachelor and Master level. In 2020 he was lecturer for the PhD course “Applied Quantum Machine Learning”. Since 2014 he has worked as an expert in quality assurance of higher education institutions and was involved in several accreditation visits for the National Agency for the Evaluation of the University system and Research (ANVUR) and for the QUACING agency for EUR-ACE accreditation of engineering courses. He was also involved in some international evaluations of european universities for Horizon2020 and Erasmus+ projects with the agencies NVAO and AQU Catalunya. He is a member of the international experts register of the agencies AIKA and THEQC. From 2011 to 2014 he was a member of various university’s commissions involved in quality assurance processes.
