Martino Trevisan

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I received my M.Sc. (2015) and Phd (2019) in Computer Science from Politecnico di Torino, both cum laude. During my master degree, I visited Télécom ParisTech for six months, working on high-speed traffic capture and analysis. I am currently an assistant professor in the same university, where I joined the SmartData Center. I participated in two research projects in collaboration with Cisco Systems working on Traffic Classification and Anomaly Detection, and I visited Cisco labs twice for short internships. I’m part of the project BigDAMA funded by the Vienna Science and Technology Fund (WWTF) through project ICT15-129. In 2018 I visited AT&T labs in Bedminster (USA) in the context of a research project about Quality of Experience monitoring. In 2018, I visited the Universidade Federal de Minas Gerais, Brazil, working for three months on anomaly detection in social network data. Currently, I am the leader of the WP2 “Tools to improve users’ privacy” of the H2020 European Project PIMCity.

My research interests are mainly focused on big data methodologies for Web and Internet analysis. My interests include designing big data algorithms to extract knowledge from large datasets of unstructured data coming from heterogeneous sources including network measurements, social networks and the Web at large. I have special attention to data privacy, working in the development of novel methodologies for private data sharing.
In my research, I leverage Machine Learning and Big Data methodologies to mine knowledge from large and distributed datasets, using state-of-the-art platforms like Apache Spark and Tensor Flow.
Other research interests include Anomaly Detection, Software Defined Networking and online social networks.