Giannotti Fosca

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Fosca Giannotti is Full Professor at Scuola Normale Superiore, Pisa, Italy. Fosca Giannotti is a pioneering scientist in mobility data mining, social network analysis and privacy-preserving data mining. Fosca leads the Pisa KDD Lab - Knowledge Discovery and Data Mining Laboratory, a joint research initiative of the University of Pisa and ISTI-CNR, founded in 1994 as one of the earliest research lab on data mining. Fosca's research focus is on social mining from big data: smart cities, human dynamics, social and economic networks, ethics and trust, diffusion of innovations. She is author of more than 300 papers. She has coordinated tens of European projects and industrial collaborations. Fosca is the former coordinator of SoBigData, the European research infrastructure on Big Data Analytics and Social Mining, an ecosystem of ten cutting edge European research centres providing an open platform for interdisciplinary data science and data-driven innovation. Recently she became the recipient of a prestigious ERC Advanced Grant entitled XAI – Science and technology for the explanation of AI decision making.

Topics: 
Contraint-Based Frequent Pattern Mining
Mobility Data Mining
Privacy-Preserving Data Mining
Complex Network Analysis and Mining
Data Mining
1989-1990 Visiting Scientist at MCC, Microelectronics and Computer Technology Corporation, Austin (USA)
1993 Visiting Scientist at CWI Amsterdam
1995 Visiting Scientist at UCLA
2006 Visiting scientist at UCLA
2006-2009 National Coordinator of the ICT Department of CNR, Area Data Mining and Semantic Web
2009-2010 Visiting scientist at Barabasi Lab (Center for Complex Network Research) of Northeastern University, Boston (USA)
2004 Co-Chair of ECML/PKDD
2008 Program Chair of ICDM
1982 Master Degree in Computer Science at University of Pisa with 110/100 cum laude

Publications

2020

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Blog

IA generativa: opportunità, rischi e regole

IA generativa: opportunità, rischi e regole di una rivoluzione già in corso, Impatto sulla società, le opportunità e l’urgenza di regole chiare

Perché dobbiamo avere un uso responsabile dell'intelligenza artificiale?

I sistemi di Intelligenza artificiale suggeriscono decisioni sulla base di pattern e regole imparate dai dati. I dati registrano l’esperienza passata e quindi contengono tutto il bene e tutto il male dell’esperienza.

The new national PhD program in Artificial Intelligence is on the launchpad! https://phd-ai.it/en/

Premio Internazionale Tecnovisionarie® 2021

Il premio Le Tecnovisionarie 2021 sul tema Intelligenza Artificiale BigData è stato consegnato a Fosca Giannotti dalla Presidente del CNR con la seguente motivazione:

Explainable Machine Learning for Trustworthy AI

Black box AI systems for automated decision making, often based on machine learning over (big) data, map a user’s features into a class or a score without exposing the reasons why.

FALLING WALLS CIRCLE TABLE: UNDERSTANDING THE SCIENTIFIC METHOD IN THE 21ST CENTURY

Against the background of the Covid-19 pandemic, which proves to provide fertile ground to intensify the ‘information disorder’ characterised by conspiracy theories and ‘alternative facts’, it is vital to underline the relevance of science and the

Il KDD-Lab, laboratorio congiunto tra Cnr e Università di Pisa, insieme con Windtre, l’Istituto Superiore di Sanità, la Fondazione Bruno Kessler e altri centri di ricerca italiani ed internazionali, ha analizzato la relazione tra la mobilità dei c

Yesterday the Italian Ministry for Technological Innovation and Digitization has established a new Task Force for the Covid-19 Emergency.

The ERC Advanced Grant XAI “Science & technology for the eXplanation of AI decision making”, led by Fosca Giannotti of the Italian CNR, in collaboration with the PhD program in “Data Science” by Scuola Normale Superiore in Pisa, invites applic

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