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Data management and modeling for improved system design and user privacy

Nicolas Kourtellis, Research Scientist in the Telefonica R&D team in Barcelona
12 Nov 2019 - 11:00 (Madrid Time)

MR-1S1 [Torres] & MR-1S3 [Quevedo], IMDEA Networks Institute, Avda. del Mar Mediterráneo 22, 28918 Leganés (Madrid)

In the present information era, user data are constantly produced by diverse and distributed sources, and collected by large-scale data management systems for modeling, using advanced machine learning (ML) methods. Detecting and understanding trends hidden in the analyzed data is crucial for optimizing system design, as well as building accurate ML-based methods for protecting the users - producers of such data.

In this talk, I will cover some of our efforts to extract data properties using graph mining and machine learning modeling, for different goals such as improving distributed system performance and workload balancing, detecting aggressive behavior in online social media, as well as enabling end-user tools for improved transparency in online advertising, while protecting user anonymity and privacy.

About Nicolas Kourtellis

Dr. Nicolas Kourtellis is a Research Scientist in the Telefonica R&D team, in Barcelona. Previously he was a Postdoctoral Researcher in the Web Mining Research Group at Yahoo Labs, in Barcelona. He holds a Ph.D. in Computer Science and Engineering from the University of South Florida (2012), a MSc in Computer Science from the University of South Florida (2008), and a BSc in Electrical and Computer Engineering from the National Technical University of Athens, Greece (2006).

His primary interests lie 1) in the web transparency, user online privacy, leakage of personal data to the online advertising ecosystem and other entities, 2) analysis and characterization of online user behavior, with respect to different dimensions such as: aggressive, abusive or cheating behavior, fake news propagation, fringe online communities, propagation of disturbing video content, etc., 3) system design for streaming data analysis and graph mining on distributed streaming processing engines.

He has published more than 60 papers, and presented his work in top academic conferences and journals such as IEEE TKDE, IEEE TPDS, IEEE ICDE, ACM KDD, ACM WWW, ACM IMC, ACM/IFIP/USENIX Middleware, etc., as well as industry-oriented conferences such as Apache BigData in Europe and N. America. He has served in many program committees of top conferences and journals (e.g., WWW, KDD, CIKM, ACM TKDD, IEEE TKDE, IEEE TPDS, etc.).

This event will be conducted in English

Organization: 

NETCOM Research Group (Telematics Engineering Department, UC3M); IMDEA Networks Institute