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个人简介
In 20 years of research, his research interests covered Big Data, Stream Processing, Semantic technologies, Data Science, Web Information Retrieval, and Service Oriented Architectures. He started the stream reasoning research field positioning it at the intersection between Stream Processing and Artificial Intelligence.
He focused the research community’s interest on this theme through a number of personal initiatives (workshops, projects, journal papers) that contributed to establishing Stream Reasoning as a recognized research and industrial sector. In the Big Data era, it is a method to tame simultaneously the velocity (analysing data streams to enable real-time decisions) and variety (integrating heterogeneous data) dimensions of Big Data. The semantic and syntactic extensions, which he proposed to the Semantic Web stack (i.e., RDF streams and Continuous SPARQL), are currently on the path towards standardization at a W3C in the RDF Stream Processing community group. In the last four years, the two main conferences on Semantic Web (ISWC and ESWC) dedicated a track to data stream to create a forum for Stream Reasoning research. Starting from 2011, he organized more than 15 tutorials and workshops on Stream Reasoning. The open source Stream Reasoner engine developed at Politecnico di Milano (namely, C-SPARQL Engine) was downloaded more than 9,000 times and it is currently maintained by Politecnico di Milano, the University of Zurich and the Insight Center of the National University of Ireland. His work on Stream Reasoning was applied in analysing Social Media, Mobile Telecom and IoT data streams in collaboration with Telecom Italia, IBM, Siemens, Oracle, Indra, and Statoil.
He focused the research community’s interest on this theme through a number of personal initiatives (workshops, projects, journal papers) that contributed to establishing Stream Reasoning as a recognized research and industrial sector. In the Big Data era, it is a method to tame simultaneously the velocity (analysing data streams to enable real-time decisions) and variety (integrating heterogeneous data) dimensions of Big Data. The semantic and syntactic extensions, which he proposed to the Semantic Web stack (i.e., RDF streams and Continuous SPARQL), are currently on the path towards standardization at a W3C in the RDF Stream Processing community group. In the last four years, the two main conferences on Semantic Web (ISWC and ESWC) dedicated a track to data stream to create a forum for Stream Reasoning research. Starting from 2011, he organized more than 15 tutorials and workshops on Stream Reasoning. The open source Stream Reasoner engine developed at Politecnico di Milano (namely, C-SPARQL Engine) was downloaded more than 9,000 times and it is currently maintained by Politecnico di Milano, the University of Zurich and the Insight Center of the National University of Ireland. His work on Stream Reasoning was applied in analysing Social Media, Mobile Telecom and IoT data streams in collaboration with Telecom Italia, IBM, Siemens, Oracle, Indra, and Statoil.
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Springer eBookspp.1-7, (2023)
PAKDD (4)pp.328-340, (2023)
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2023 IEEE International Conference on Big Data (BigData)pp.5156-5165, (2023)
Springer eBookspp.69-107, (2022)
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Springer eBookspp.41-67, (2022)
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Information Systems (2022)
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Springer eBookspp.109-138, (2022)
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