Alessio Bernardo

After obtaining his PhD at the Politecnico di Milano, at the Department of Electronics, Information and Bioengineering, under the supervision of Prof. Emanuele Della Valle, with a thesis entitled ’On Learning from Massive, Evolving, and Imbalanced Data Streams’, Alessio Bernardo is a Research Fellow at the same department. His research interests are Streaming Machine Learning, Evolving Data Streams, Concept Drift, Class Imbalance, and Streaming Edge AI.

Publications

If you are looking for a pdf for one of these publications, take a look at my research gate profile. Another option is my google scholar profile.

Last update on October 2023.

2022

Towards Time-Evolving Analytics: Online Learning for Time-Dependent Evolving Data Streams. G Ziffer, A Bernardo, E Della Valle, V Cerqueira, A Bifet. Journal of Data Science, IOS Press, 2022.
An extensive study of C-SMOTE, a Continuous Synthetic Minority Oversampling Technique for Evolving Data Streams. A Bernardo, E Della Valle. Journal of Expert Systems with Applications, 2022.

2021

SMOTE-OB: Combining SMOTE and Online Bagging for Continuous Rebalancing of Evolving Data Streams. A Bernardo, E Della Valle. IEEE International Conference on Big Data (Big Data), 2021.
Kalman Filtering for Learning with Evolving Data Streams. G Ziffer, A Bernardo, E Della Valle, A Bifet. IEEE International Conference on Big Data (Big Data), 2021.
IEBench: Benchmarking Streaming Learners on Imbalanced Evolving Data Streams. A Bernardo, G Ziffer, E Della Valle. (2021, December). IEEE International Conference on Data Mining Workshops (ICDMW), 2021.
VFC-SMOTE: Very Fast Continuous Synthetic Minority Oversampling for Evolving Data Streams. A Bernardo, E Della Valle. Journal of Data Mining and Knowledge Discovery (DAMI) special issue at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2021.
Predict COVID-19 Spreading With C-SMOTE. A Bernardo, E Della Valle. International Conference on Business Information Systems (BIS), 2021.
Supporting an Expert-centric Process of New Product Introduction With Statistical Machine Learning. S Zahmatkesh, A Bernardo, E Falzone, E Carena, E Della Valle. International Conference on Business Information Systems (BIS), 2021.

2020

C-SMOTE: Continuous Synthetic Minority Oversampling for Evolving Data Streams. A Bernardo, H M Gomes, J Montiel, B Pfahringer, E Della Valle, A Bifet. IEEE International Conference on Big Data (Big Data), 2020.
Incremental Rebalancing Learning on Evolving Data Streams. A Bernardo, E Della Valle, A Bifet. IEEE International Conference on Data Mining Workshops (ICDMW), 2020.
Fast Incremental Naïve Bayes with Kalman Filtering. G. Ziffer, A Bernardo, E Della Valle, A Bifet. IEEE International Conference on Data Mining Workshops (ICDMW), 2020.