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Paolo Ferragina joins L'EMbeDS as Full Professor in Computer Science

Welcome to Paolo Ferragina, whose ground-breaking methodological research and multifaceted applied projects will significantly enrich our community and expand its reach
Publication date: 26.06.2024
Paolo Ferragina
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Paolo Ferragina joined L'EMbeDS and the Class of Social Sciences of the Sant'Anna School in June 2024.

Paolo Ferragina is a Full Professor in Computer Science, recruited by the Department of Excellence through a special call published in February 2024.

He graduated in Computer Science at the University of Pisa (1992, cum laude), obtained a Ph.D. in Computer Science from the same University (1996) and pursued his post-doctoral studies at the Max-Planck Institut fur Informatik (1997-98). Notably, when he first became Full Professor of Computer Science in 2007 at the University of Pisa, his promotion was sponsored for five years (2007-2011) by Yahoo!.

Paolo Ferragina's research interests concern the design and implementation of algorithms and data structures for compressing, indexing, searching, and mining Big Data. Over time, his activities led him to important collaborations with Senseable City Lab at MIT (Boston, USA), Pinello Lab at Harvard and MassGeneral Hospital (Boston, USA), European Broadcasting Union (EBU), Google (Zurich), Bloomberg (London), ST Microelectronics, Tiscali (Istella's search engine), Yahoo! Research (Barcelona), Bassilichi, CERVED Group, ENEL Foundation, SadasDB, Spazio Dati, etc.

He is currently also a member of the Scientific Advisory Committee of the CNR national department on "Engineering, ICT, and Technologies for energy and mobility"; of the Steering Committee of the SIAM Symposium on Algorithm Engineering and Experiments; of the Steering Committee of the Ph.D. in Computer Science of the Universities of Pisa-Florence-Siena; of the Scientific Board of the National Ph.D. in Artificial Intelligence for Society; of the Advisory Board of the Master in "Big Data Analytics & Artificial Intelligence for Society''; and of the Working Group on  "AI and Justice'', established by the Italian Ministry of Justice. Paolo is also the co-director of the International Ph.D. School "Jacob T. Schwartz'' on ``Computational Social Sciences'', held every year in Lipari; an area editor of the Encyclopedia of Algorithms (Springer, Editor Ming-Yang Kao, 2016) and of the Encyclopedia of Big Data Technologies (Springer, Editor Zomaya and Sakr, 2018); and a member of the Editorial Board of the Journal on Graph Algorithms and Applications (JGAA).

At the University of Pisa, Paolo Ferragina served as Vice-Rector for ICT (2019-2022); President of the regional Ph.D. in Computer Science (2017-2020); Vice-Rector for "Applied Research and Innovation" (2010-2016); and Vice-Chair of the Department of Computer Science (2006-2010).

Paolo Ferragina is the (co-)recipient of some international awards, among the most recent ones we mention: two Test of Time awards assigned in 2023 by the “European Symposium on Algorithms (ESA)” and the “ACM Conference on Information and Knowledge Management CIKM)”, and the ``2022 ACM Paris Kanellakis from theory to practice" award for the discovery of the FM-index.

What are Paolo Ferragina’s plans for this new chapter of her academic career, in connection with the objectives of  L'EMbeDS?"I’m excited to be part of the multi-disciplinary environment and research opportunities offered by L’EMbeDS and, hopefully, contribute to amplifying its research and tech-transfer strategies via the consolidation and empowerment of its Computer Science leadership, especially in the support that Algorithmics and AI can provide to Data Science over multi-modal big data. In fact, too many times I’ve heard euphoric tones about the availability of data, but big data just means “big data” with a consequent increase in the costs of storage, governance, searching, and, more importantly, extracting “value” from them. It is therefore not surprising that today, more than ever before, we need to build novel data-intensive platforms that are not only efficient and effective but also usable by everyone in a safe, sustainable, private and trustworthy way, thus allowing to turn large collections of private/public data into more value, and thus more benefit for all of us.”