The Big and Open Data Innovation Laboratory (BODaI-Lab) of the University of Brescia, Italy, aims to create working groups that develop – within specific projects – innovative methods, techniques and tools for the retrieval, management and analysis of open and big data with a multidisciplinary approach.
The main purpose is to support research within the University of Brescia, in the fields of medical, engineering, economic, financial, business, social and legal scientific research. Particular attention is devoted to technology transfer to the PA and the Industry sector.
Bodai (ぼだい) is the Japanese version of the Sanskrit bodhi (बोधि). It is the state of the completely enlightened mind, i.e. the knowledge or wisdom, or awakened intellect, of a Buddha.
The verbal root budh- means to awaken. This term, although mostly used the context of Buddhism, is also present in other Eastern philosophies and traditions. It has been popularised in the Western world with the word enlightenment, having the connotation of a sudden insight into a transcendental truth or reality
In our Laboratory, wisdom, knowledge of Nature and enlightenment are achieved through data analysis and machine learning algorithms.
The symbol used for the “O” of BODaI (as well as for the “O”s in the BODaI’s projects logos) is the sacred symbol in Zen Buddhism called enso, literally meaning circle. It symbolizes absolute enlightenment, strength, elegance, the beginning and end of all things, the circle of life and the connectedness of existence. In two words, Universe and Nature. At the same time, through the impossibility of creating the perfect circle freehand, it contains the lesson of the limits of the human mind and the acceptance of imperfection as perfect.
Some authors consider enso as a precursor of the mathematical symbol of infinity.
BODaI-Lab deals with developing methods, models and advanced techniques of multivariate statistical data analysis, machine learning, artificial intelligence, semantic and social web, useful for research, organization, classification, integration, analysis and visualization of huge, heterogeneous and complex collections of digital data (big data), even in open format (open data).
The research activity of the laboratory is focused on the following themes:
Scientific coordinators: Paola Zuccolotto and Marica Manisera
Scientific coordinators: Eugenio Brentari and Luigi Odello
Scientific coordinator: Devis Bianchini
Scientific coordinator: Stefano Calza
The project aims at developing machine learning methods and tools for Variable Importance Measurement (VIM) and Variable Selection in statistical prediction problems. The topic is analyzed from a methodological and empirical point of view; specific computational functions are built for the new proposed procedures. From the point of view of the methods, the main focus is on ensemble learning techniques.
Scientific coordinators: Paola Zuccolotto, Marco Sandri
View project
The project is carried out in collaboration with researchers of the Department of Biotechnology, University of Verona. Microarray and RNA-Seq gene expression data in grapevine are analyzed with statistical methods and data mining/machine learning algorithms in order to detect associations and relationships with reference to genotype, environment, developmental stages and interactions among them.
Scientific coordinators: Paola Zuccolotto, Marco Sandri
Scientific coordinator: Devis Bianchini
The project is part of the actions aimed at contrasting Covid-19 infection through the development of prognostic risk models based on quantitative data related to lung damage and biochemical tests, detected in 1300 patients affected by Covid-19 in course of hospitalization at ASST Spedali Civili Brescia. Lung damage assessment is performed by Brixia-severity radiological score and the state of tissue inflammation through the biochemical data PCR, ferritin, LDH, troponin, D-Dimer, fibrinogen, WBC. The methods are based on multivariate statistical analysis, data mining and artificial intelligence algorithms.
Scientific coordinators: Roberto Maroldi, Alfonso Gerevini, Paola Zuccolotto
The project, developed by the DMS StatLab of the University of Brescia in agreement with the Statistical Office of the Municipality of Brescia, is based on the use of high frequency mobile phone data to develop spatio-temporal indicators useful for statistical analyses.
Participants: Anna Simonetto, Rodolfo Metulini, Marie Cointin
Scientific coordinator: Maurizio Carpita
This project is developed in cooperation with Regione Lombardia, aiming at investigating techniques for exploration and knowledge extraction from Open Data (in particular, focusing on data about mobility) provided by Regione Lombardia on its official web portal (http://www.dati.lombardia.it).
Scientific coordinator: Devis Bianchini
Project developed within the two-years agreement between University of Brescia, Università Cattolica in Brescia and A2A S.p.A. The project will provide essential information for preparing A2A initiative for vulnerable consumers. In particular, the project includes both support for the identification of potential beneficiars and the implementation of field experiments to identify more effective procedures aiming at stimulating contributions to the project from consumers.
Scientific coordinator: Raffaele Miniaci
Scientific coordinator: Raffaele Miniaci