Pedreschi Dino

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Dino Pedreschi is a Professor of Computer Science at the University of Pisa, and a pioneering scientist in mobility data mining, social network mining and privacy-preserving data mining. He co-leads with Fosca Giannotti the Pisa KDD Lab - Knowledge Discovery and Data Mining Laboratory, a joint research initiative of the University of Pisa and the Information Science and Technology Institute of the Italian National Research Council, one of the earliest research lab centered on data mining. His research focus is on big data analytics and mining and their impact on society. He is a founder of the Business Informatics MSc program at Univ. Pisa, a course targeted at the education of interdisciplinary data scientists. Dino has been a visiting scientist at Barabasi Lab (Center for Complex Network Research) of Northeastern University, Boston (2009-2010), and earlier at the University of Texas at Austin (1989-90), at CWI Amsterdam (1993) and at UCLA (1995). In 2009, Dino received a Google Research Award for his research on privacy-preserving data mining.
Topics: 
Big Data Analytics
Social Network Analysis and Mining
Analysis of Human Mobility
Privacy-by-Design and Ethical Data Mining
Nowcasting of Socio-Economic Indicators
Complex Network Dynamics
Data Mining and Knowledge Discovery
Privacy Preserving Data Mining
Constraint-Based Pattern Discovery
Data Mining Query Language
Market Basket Analysis
Fraud Detection
Logic in Databases
Non Monotonic Non Deterministic Temporal Reasoning
Deductive and Object-Oriented Databases
Formal Methods
Logic Programming
2009 Google Research Award on Privacy
2017 University of Pisa Ordine del Cherubino
1989-1990 Visiting scientist at University of Texas, Austin
1993 Visiting scientist at CWI Amsterdam
1995 Visiting scientist at UCLA
2009-2010 Visiting scientist at Barabasi Lab (Center for Complex Network Research) of Northeastern University, Boston
2004 Co-Chair of ECML/PKDD
2005 Vice-Chair of ICDM
2014 Vice-Chair of ICDE
1987 Ph.D. in Computer Science at University of Pisa
Position
Full Professor
Affiliation
Department of Computer Science, University of Pisa (DI-UNIPI)
Room
318
Phone
+39 050 221 2752
Email
Homepage
Google Scholar
Dino Pedreschi on Google Scholar
DBLP
Dino Pedreschi on DBLP
Scopus
Dino Pedreschi on Scopus
ArnetMiner
Dino Pedreschi on ArnetMiner
Twitter
Dino Pedreschi on Twitter

Publications

2018

Pages

Blog

Carpooling, i.e., the act where two or more travelers share the same car for a common trip, is one of the possibilities brought forward to reduce traffic and its externalities, but experience shows that it is difficult to boost the adoption of car

Clustering Individual Transactional Data for Masses of Users

Mining a large number of datasets recording human activities for making sense of individual data is the key enabler of a new wave of personalized knowledge-based services.

ISTI News June 2017

On the second issue of the ISTI News newsletter you'll find a description of the new Ph.D.

Data Science - 16 giugno 2016

The increasing interest on data science from both the academic and industrial worlds led to the creation of a brand new Ph.D.

Data Driven Life Workshop

The European Data Protection Supervisor has invited Dino Pedreschi to a panel on the ethical aspects related to Smart Cities, during the Data Driven Life Workshop

I paesaggi digitali dei Big Data | Dino Pedreschi | TEDxManciano

La rivoluzione digitale sta abbattendo la distanza fra il mondo fisico e quello "online".

Today at the Aula Magna of Polo Fibonacci in Pisa, Dino Pedreschi has been awarded the Ordine del Cherubino by the Rector of the University of Pisa.

At the "Measuring Migrations" workshop, a side event of the NTTS2017 conference, Fosca Giannotti, Dino Pedreschi and Alina Sirbu have contributed with a talk titled "Exploring human mobility and migration

At the "Measuring Migrations" workshop, a side event of the NTTS2017 conference, Fosca Giannotti, Dino Pedreschi and Alina Sirbu have contributed with a talk titled "Exploring human mobility and migration

Dino Pedreschi on Radio Radio is talking about a study from the students of the Master in Big Data on how the TV series and Big Data can be used in order forecast th

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