Roberto Corizzo, Ph.D, is a Research Fellow at the Dept. of Computer Science, University of Bari, Italy. He has served on the Program Committees of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) and the International Symposium on Methodologies for Intelligent Systems (ISMIS). He has been a Research Intern at the INESC TEC research institute in Porto (Portugal) under the supervision of Prof. Joao Gama, and at the American University in Washington D.C. under the supervision of Prof. Nathalie Japkowicz. His research interests include big data analytics, data mining and predictive modeling techniques for sensor networks.

Research Interests

Big data analytics, Data Mining, Predictive Modeling Techniques for Sensor Networks, Energy Prediction in Smart Grids, Anomaly Detection

Roberto Corizzo
PhD, External Collaborator
em@il: roberto.corizzo @ uniba.it
webpage: http://www.di.uniba.it/~corizzo





Publications Legend

Journal Articles
Book
Conference or Workshop
Editorship
Collection
Other

Publications


2020

Jonathan Kaufmann, Kathryn Asalone, Roberto Corizzo, Colin Saldanha, John Bracht, Nathalie Japkowicz:
One-Class Ensembles for Rare Genomic Sequences Identification. DS: 340-354 (2020)
DOI: https://doi.org/10.1007/978-3-030-61527-7_23
Mirche Arsov, Eftim Zdravevski, Petre Lameski, Roberto Corizzo, Nikola Koteli, Kosta Mitreski, Vladimir Trajkovik:
Short-term air pollution forecasting based on environmental factors and deep learning models. FedCSIS: 15-22 (2020)
DOI: https://doi.org/10.15439/2020F211
Michelangelo Ceci, Roberto Corizzo, Nathalie Japkowicz, Paolo Mignone, Gianvito Pio:
ECHAD: Embedding-Based Change Detection From Multivariate Time Series in Smart Grids. IEEE Access 8: 156053-156 (2020)
DOI: https://doi.org/10.1109/ACCESS.2020.3019095
Biserka Petrovska, Eftim Zdravevski, Petre Lameski, Roberto Corizzo, Ivan Stajduhar, Jonatan Lerga:
Deep Learning for Feature Extraction in Remote Sensing: A Case-Study of Aerial Scene Classification. Sensors 20(14): 3906 (2020)
DOI: https://doi.org/10.3390/s20143906
Roberto Corizzo, Michelangelo Ceci, Eftim Zdravevski, Nathalie Japkowicz:
Scalable auto-encoders for gravitational waves detection from time series data. Expert Syst. Appl. 151: 113378 (2020)
DOI: https://doi.org/10.1016/j.eswa.2020.113378


2019

Sid Ryan, Roberto Corizzo, Iluju Kiringa, Nathalie Japkowicz:
Deep Learning Versus Conventional Learning in Data Streams with Concept Drifts. ICMLA: 1306-1313 (2019)
DOI: https://doi.org/10.1109/ICMLA.2019.00213
Sid Ryan, Roberto Corizzo, Iluju Kiringa, Nathalie Japkowicz:
Pattern and Anomaly Localization in Complex and Dynamic Data. ICMLA: 1756-1763 (2019)
DOI: https://doi.org/10.1109/ICMLA.2019.00285
Roberto Corizzo, Michelangelo Ceci, Donato Malerba:
Big Data Analytics and Predictive Modeling Approaches for the Energy Sector. BigData Congress: 55-63 (2019)
DOI: https://doi.org/10.1109/BigDataCongress.2019.00020
Roberto Corizzo, Michelangelo Ceci, Nathalie Japkowicz:
Anomaly Detection and Repair for Accurate Predictions in Geo-distributed Big Data. Big Data Research 16: 18-35 (2019)
DOI: https://doi.org/10.1016/j.bdr.2019.04.001
Ameya Malondkar, Roberto Corizzo, Iluju Kiringa, Michelangelo Ceci, Nathalie Japkowicz:
Spark-GHSOM: Growing Hierarchical Self-Organizing Map for large scale mixed attribute datasets. Inf. Sci. 496: 572-591 (2019)
DOI: https://doi.org/10.1016/j.ins.2018.12.007
Roberto Corizzo, Gianvito Pio, Michelangelo Ceci, Donato Malerba:
DENCAST: distributed density-based clustering for multi-target regression. J. Big Data 6: 43 (2019)
DOI: https://doi.org/10.1186/s40537-019-0207-2
Michelangelo Ceci, Roberto Corizzo, Donato Malerba, Aleksandra Rashkovska:
Spatial autocorrelation and entropy for renewable energy forecasting. Data Min. Knowl. Discov. 33(3): 698-729 (2019)
DOI: https://doi.org/10.1007/s10618-018-0605-7


2018

Domenico Redavid, Roberto Corizzo, Donato Malerba:
An OWL Ontology for Supporting Semantic Services in Big Data Platforms. BigData Congress: 228-231 (2018)
DOI: https://doi.org/10.1109/BigDataCongress.2018.00039


2017

Michelangelo Ceci, Roberto Corizzo, Fabio Fumarola, Donato Malerba, Aleksandra Rashkovska:
Predictive Modeling of PV Energy Production: How to Set Up the Learning Task for a Better Prediction? IEEE Trans. Industrial Informatics 13(3): 956-966 (2017)
DOI: https://doi.org/10.1109/TII.2016.2604758
Roberto Corizzo, Dino Ienco:
Proceedings of the ECML/PKDD Discovery Challenges co-located with European Conference on Machine Learning - Principle and Practice of Knowledge Discovery in Database (ECML PKDD 2017), Skopje, Macedonia, September 18, 2017. DC@PKDD/ECML CEUR Workshop Proceedings 1972, CEUR-WS.org (2017)
DOI: http://ceur-ws.org/Vol-1972
Roberto Corizzo, Gianvito Pio, Michelangelo Ceci, Donato Malerba:
Forecasting via Distributed Density-Based Clustering. SEBD: 57 (2017)
DOI: http://ceur-ws.org/Vol-2037/paper_10.pdf


2015

Michelangelo Ceci, Roberto Corizzo, Fabio Fumarola, Michele Ianni, Donato Malerba, Gaspare Maria, Elio Masciari, Marco Oliverio, Aleksandra Rashkovska:
Big Data Techniques For Supporting Accurate Predictions of Energy Production From Renewable Sources. IDEAS: 62-71 (2015)
DOI: https://doi.org/10.1145/2790755.2790762
Michelangelo Ceci, Roberto Corizzo, Fabio Fumarola, Michele Ianni, Donato Malerba, Gaspare Maria, Elio Masciari, Marco Oliverio, Aleksandra Rashkovska:
VIPOC Project Research Summary (Discussion Paper). SEBD: 208-215 (2015)


2014

Michelangelo Ceci, Nunziato Cassavia, Roberto Corizzo, Pietro Dicosta, Donato Malerba, Gaspare Maria, Elio Masciari, Camillo Pastura:
Innovative power operating center management exploiting big data techniques. IDEAS: 326-329 (2014)
DOI: https://doi.org/10.1145/2628194.2628231
Michelangelo Ceci, Nunziato Cassavia, Roberto Corizzo, Pietro Dicosta, Donato Malerba, Gaspare Maria, Elio Masciari, Camillo Pastura:
Big Data Techniques For Renewable Energy Market. SEBD: 369-377 (2014)