Our Lab

The Knowledge Discovery and Data Mining Laboratory (KDD Lab) is a joint research initiative of ISTI Institute of CNR and the Department of Computer Science of the University of Pisa.

The objective of the research unit is the development of theory, techniques and systems for extracting and delivering useful knowledge out of large masses of data.

Today, knowledge discovery and data mining is both a technology that blends data analysis methods with sophisticated algorithms for processing large data sets, and an active research field that aims at developing new data analysis methods for novel forms of data. On one side, classification, clustering and pattern discovery tools are now part of mature data analysis and Business Intelligence systems and have been successfully applied to problems in various commercial and scientific domains. On the other side, the increasing heterogeneity and complexity of the new forms of data – such as those arriving from medicine, biology, the Web, the Earth observation systems, the mobility data arriving from wireless networks – call for new forms of patterns and models, together with new algorithms to discover such patterns and models efficiently.

In this context, the mission of the KDD laboratory is to pursue fundamental research, strategic applications and higher education.


It was 1999 when we approached data mining research field. Our exploration of the world of Data is still continuing...

Applied Data Science and Visual Analytics

Data Science aims at discovering patterns and models of human behavior across the various social dimensions, extracting multi-dimensional patterns and models from a vast variety of social data.
Data Science may have a potentially high impact and may generate enormous value to society. It can create new opportunities to understand complex aspects, such as mobility behaviors, economic and financial crises, the spread of epidemics, the diffusion of opinions and so on.

Mobility Data Mining for Science of Cities

The large diffusion of localization technologies and location-based services is leading to the production of large and diversified traces of human mobility, containing the potential to infer models of unprecedented precision and depth. They can be key enablers of many applications, from monitoring urban traffic features to reconstruct inter-city mobility demands and region-scale structures, which could help in making modern urban spaces more sustainable, efficient and comfortable for citizens.

Social Network Analysis and Network Science

The main research track of KDDLab in the field of Complex Networks is Multidimensional Network Analysis. Traditionally, Complex Network Analysis has been monodimensional: researchers focused their attention to network with a single kind of relation represented. KDDLab is pushing the research over multidimensional networks, i.e. network with multiple kind of relations, since they are a better model to represent the complexity in reality (transportation, infrastructure and social networks are often multidimensional).

Ethical, Trustworthy, Interactive AI

In the era of Big Data person-specific data are increasingly collected, stored and analyzed by modern organizations.
These data typically describe different dimensions of the daily social life and are the heart of a knowledge society, where the understanding of complex social phenomena is sustained by the knowledge extracted from the miners of big data across the various social dimensions by using data mining, machine learning and AI technologies.

Analytical Platforms and Infrastructures for Social Mining

One of the most pressing and fascinating challenges scientists face today, is understanding the complexity of our globally interconnected society. The big data arising from the digital breadcrumbs of human activities promise to let us scrutinize the ground truth of individual and collective behaviour at an unprecedented detail and scale. There is an urgent need to harness these opportunities for scientific advancement and for the social good. The main obstacle to this accomplishment, besides the scarcity of data scientists, is the lack of a large-scale open infrastructure, where big data and social mining research can be carried out.

Symposium on Intelligent Data Analysis - IDA2024

2024/04/24 02:00 Europe/Rome
2024/04/26 02:00 Europe/Rome
Stockholm, Sweden
Symposium on Intelligent Data Analysis (IDA 2024)

Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation. Therefore IDA accepts all inspiring papers for both presentation and publication. In order to create an open atmosphere that encourages discussion, the IDA symposium is intentionally small-scale and single-track.

2nd International SoBigData Summer School - Empowering Data for Social Good

2024/06/16 02:00 Europe/Rome
2024/06/22 02:00 Europe/Rome
Baratti, Livorno, Italy
2nd International SoBigData Summer School

The 2024 edition of the SoBigData summer school will focus on how data can be used for social good, and this topic will be explored around five different thematic areas: European Framework and Communities, Trustworthy and Ethical AI, Ecology and Green development, Health, Technology and AI.

MAURO 2024 - 1st International Workshop on Impact of Algorithms and Services on the Urban Ecosystem

2024/06/24 02:00 Europe/Rome
2024/06/24 02:00 Europe/Rome
Brussels, Belgium
1st International Workshop on Impact of Algorithms and Services on the Urban Ecosystem

As cities worldwide are becoming increasingly interconnected and technologically advanced, it is crucial to explore the implications of algorithmic decision-making and AI applications on urban environments. The proposed workshop aims to delve into the profound influence of algorithms (AI in particular), platforms and services on the structure and dynamics of the urban ecosystem.

UKDE 2024 - 1st International Workshop on User-Centered Practices of Knowledge Discovery in Educational Data

2024/07/01 02:00 Europe/Rome
2024/07/04 02:00 Europe/Rome
Cagliari, Sardinia, Italy
UKDE 2024

The increasing amount of learning data, originated from a variety of learning contexts (e.g., Massive Open Online Courses - MOOCs, intelligent tutoring systems, and flipped classroom courses) is soliciting interesting educational research questions. Notable research directions include exploring and understanding how students learn and how people teach, as well as developing strategies for supporting learners and teachers effectively.


Fun Facts

Gigabytes of data produced by a single person each year
Millions of Internet users
Millions of Tweets sent per day
Gigabytes of Internet traffic per day


Need info? Want ideas? Write us!

Address @ ISTI

Istituto di Scienza e Tecnologie dell’Informazione
Area della Ricerca CNR
via G. Moruzzi 1
56124 Pisa, Italy

Address @ UniPi

Dipartimento di Informatica
Università di Pisa
Largo B. Pontecorvo 3
56127 Pisa, Italy

Phone Number

Phone: +39 050 621 3013
Fax: +39 050 315 2040