Ileana Baldi holds a PhD in Statistics from the University of Milano-Bicocca and an MSc in Epidemiology from the University of Torino. She is Associate Professor of Medical Statistics at the Unit of Biostatistics Epidemiology and Public Health, Dept. of Cardiac, Thoracic, Vascular Sciences and Public Health at the University of Padova (UNIPD), where she has been a Faculty member since 2011. During her previous research experience at the University of Torino (2002-2011), she has developed skills in the design of clinical trials and analysis of electronic health sources, through participation in a series of studies that examine health outcomes at the population level. Prof. Baldi's recent research interests encompass using Machine Learning techniques to address the analytical challenges posed by Big Data, particularly data flows from mobile devices and wearable technologies, up to the most traditional electronic health data and textual sources. Recently, she has been the principal investigator of four projects based on Big Data or Machine Learning, three funded by the UNIPD, and one funded by the Italian Ministry of Health. Prof. Baldi is past Director of the (Master di II Livello) advanced post-graduate course in Machine Learning at the UNIPD.
She has authored over 100 scientific publications, guest-edited two special issues, peer-reviewed for journals and conferences (i.e., APHA, AMIA, ASN), and attended several international and national congresses.
Ileana Baldi holds a PhD in Statistics from the University of Milano-Bicocca and an MSc in Epidemiology from the University of Torino. She is Associate Professor of Medical Statistics at the Unit of Biostatistics Epidemiology and Public Health, Dept. of Cardiac, Thoracic, Vascular Sciences and Public Health at the University of Padova (UNIPD), where she has been a Faculty member since 2011. During her previous research experience at the University of Torino (2002-2011), she has developed skills in the design of clinical trials and analysis of electronic health sources, through participation in a series of studies that examine health outcomes at the population level. Prof. Baldi's recent research interests encompass using Machine Learning techniques to address the analytical challenges posed by Big Data, particularly data flows from mobile devices and wearable technologies, up to the most traditional electronic health data and textual sources. Recently, she has been the principal investigator of four projects based on Big Data or Machine Learning, three funded by the UNIPD, and one funded by the Italian Ministry of Health. Prof. Baldi is past Director of the (Master di II Livello) advanced post-graduate course in Machine Learning at the UNIPD.
She has authored over 100 scientific publications, guest-edited two special issues, peer-reviewed for journals and conferences (i.e., APHA, AMIA, ASN), and attended several international and national congresses.