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<\/div><\/div>Agnese <\/span>Panzera <\/span><\/h3>
<\/div><\/div>Agnese <\/span>Panzera <\/span><\/h3>DISIA<\/div>Agnese Panzera is associate professor of Statistics at DiSIA, University of Florence. Her main research interests concern nonparametric methods for directional data and graphical models for angular variables.<\/div>Homepage<\/a><\/div><\/div><\/div><\/div>![\"Alberto](\"https:\/\/datascience.unifi.it\/wp-content\/uploads\/2023\/09\/Alberto-Cassese-112.jpg\")
<\/div><\/div>Alberto <\/span>Cassese <\/span><\/h3>DISIA - Deputy director<\/div>Alberto Cassese is an RTD-B (Assistant professor with tenure) of Statistics at DiSIA, University of Florence. His academic journey includes roles at institutions such as Rice University and Maastricht University. Alberto is dedicated to innovative statistical methodologies, driven by their practical applications in real-world scenarios. His research expertise encompasses several topics, spanning high-dimensional complex data (including -omics data), behavioral data, flu data and mass-spectrometry data.<\/div>Homepage<\/a><\/div><\/div><\/div><\/div>![\"\"](\"https:\/\/datascience.unifi.it\/wp-content\/uploads\/2019\/05\/anna.jpg\")
<\/div><\/div>Anna <\/span>Gottard <\/span><\/h3>DISIA - Director<\/div>Anna Gottard is associate professor of Statistics at DiSIA, University of Florence and Director of the Florence Center for Data Science. She serves as associate editor for the Journal of the Royal Statistical Society - Series A and for Statistical Methods & Applications. Her current research interest concerns fair\/interpretable statistical machine learning, tree-embedded models, graphical models, mixture models under latent uncertainty and multivariate models for angles and directional data.<\/div>Homepage<\/a><\/div><\/div><\/div><\/div>![\"\"](\"https:\/\/datascience.unifi.it\/wp-content\/uploads\/2023\/04\/Daniele-Castellana-300x297.jpg\")
<\/div><\/div>Daniele <\/span>Castellana <\/span><\/h3>DISIA<\/div>Daniele Castellana is an RTD-A (Research Fellow) of Computer Science at DiSIA, University of Florence. Previously, he was a researcher at the University of Pisa, where he also obtained his PhD. His main research area is Machine Learning, with emphasis on complex data (such as graphs) and probabilistic approaches.<\/div>
Agnese Panzera is associate professor of Statistics at DiSIA, University of Florence. Her main research interests concern nonparametric methods for directional data and graphical models for angular variables.<\/div>
Homepage<\/a><\/div><\/div><\/div><\/div><\/div><\/div>Alberto <\/span>Cassese <\/span><\/h3>
<\/div><\/div>Alberto <\/span>Cassese <\/span><\/h3>DISIA - Deputy director<\/div>Alberto Cassese is an RTD-B (Assistant professor with tenure) of Statistics at DiSIA, University of Florence. His academic journey includes roles at institutions such as Rice University and Maastricht University. Alberto is dedicated to innovative statistical methodologies, driven by their practical applications in real-world scenarios. His research expertise encompasses several topics, spanning high-dimensional complex data (including -omics data), behavioral data, flu data and mass-spectrometry data.<\/div>Homepage<\/a><\/div><\/div><\/div><\/div><\/div><\/div>Anna <\/span>Gottard <\/span><\/h3>DISIA - Director<\/div>Anna Gottard is associate professor of Statistics at DiSIA, University of Florence and Director of the Florence Center for Data Science. She serves as associate editor for the Journal of the Royal Statistical Society - Series A and for Statistical Methods & Applications. Her current research interest concerns fair\/interpretable statistical machine learning, tree-embedded models, graphical models, mixture models under latent uncertainty and multivariate models for angles and directional data.<\/div>Homepage<\/a><\/div><\/div><\/div><\/div><\/div><\/div>Daniele <\/span>Castellana <\/span><\/h3>DISIA<\/div>Daniele Castellana is an RTD-A (Research Fellow) of Computer Science at DiSIA, University of Florence. Previously, he was a researcher at the University of Pisa, where he also obtained his PhD. His main research area is Machine Learning, with emphasis on complex data (such as graphs) and probabilistic approaches.<\/div>
Alberto Cassese is an RTD-B (Assistant professor with tenure) of Statistics at DiSIA, University of Florence. His academic journey includes roles at institutions such as Rice University and Maastricht University. Alberto is dedicated to innovative statistical methodologies, driven by their practical applications in real-world scenarios. His research expertise encompasses several topics, spanning high-dimensional complex data (including -omics data), behavioral data, flu data and mass-spectrometry data.<\/div>
Homepage<\/a><\/div><\/div><\/div><\/div><\/div><\/div>Anna <\/span>Gottard <\/span><\/h3>
<\/div><\/div>Anna <\/span>Gottard <\/span><\/h3>DISIA - Director<\/div>Anna Gottard is associate professor of Statistics at DiSIA, University of Florence and Director of the Florence Center for Data Science. She serves as associate editor for the Journal of the Royal Statistical Society - Series A and for Statistical Methods & Applications. Her current research interest concerns fair\/interpretable statistical machine learning, tree-embedded models, graphical models, mixture models under latent uncertainty and multivariate models for angles and directional data.<\/div>Homepage<\/a><\/div><\/div><\/div><\/div><\/div><\/div>Daniele <\/span>Castellana <\/span><\/h3>DISIA<\/div>Daniele Castellana is an RTD-A (Research Fellow) of Computer Science at DiSIA, University of Florence. Previously, he was a researcher at the University of Pisa, where he also obtained his PhD. His main research area is Machine Learning, with emphasis on complex data (such as graphs) and probabilistic approaches.<\/div>
Anna Gottard is associate professor of Statistics at DiSIA, University of Florence and Director of the Florence Center for Data Science. She serves as associate editor for the Journal of the Royal Statistical Society - Series A and for Statistical Methods & Applications. Her current research interest concerns fair\/interpretable statistical machine learning, tree-embedded models, graphical models, mixture models under latent uncertainty and multivariate models for angles and directional data.<\/div>
Homepage<\/a><\/div><\/div><\/div><\/div><\/div><\/div>Daniele <\/span>Castellana <\/span><\/h3>
<\/div><\/div>Daniele <\/span>Castellana <\/span><\/h3>DISIA<\/div>Daniele Castellana is an RTD-A (Research Fellow) of Computer Science at DiSIA, University of Florence. Previously, he was a researcher at the University of Pisa, where he also obtained his PhD. His main research area is Machine Learning, with emphasis on complex data (such as graphs) and probabilistic approaches.<\/div>
Daniele Castellana is an RTD-A (Research Fellow) of Computer Science at DiSIA, University of Florence. Previously, he was a researcher at the University of Pisa, where he also obtained his PhD. His main research area is Machine Learning, with emphasis on complex data (such as graphs) and probabilistic approaches.<\/div>
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