Head of Unit

Giuseppe Jurman

Email: giuseppe.jurman@fbk.eu

Giuseppe Jurman is a mathematician, with a PhD in Algebra, working at MPBA on various aspects of computational biology. His main research interests are statistical machine learning, mathematical modeling for high-throughtput data and network analysis. He is also an expert in scientific programming with Python and other computing languages.

Senior Researchers

Shahryar Noei

Email: snoei@fbk.eu

Shahryar is a researcher in the "data science for health" unit. He has an MS in biomedical engineering from the Sharif University of technology and a Ph.D. in cognitive neuroscience from the University of Trento, focusing on the computational role of neural oscillations. His main research interest is to develop and apply machine learning techniques for clinical applications to facilitate the process of diagnosis, prognosis, and explainability.

Monica Moroni

Email: mmoroni@fbk.eu

Monica is a mathematician with previous research experience in the field of computational neuroscience. Her main research interests are the development and application of machine learning models to clinical data (imaging data, EHR) with the final goal of providing diagnostic and prognostic tools to support clinicians in their job. In her work she is organized and determined. She is passionate about science communication.

Marco Chierici

Email: chierici@fbk.eu

Marco Chierici (PhD Bioengineering, University of Padova) is a senior data scientist at DSH. His main research interests include the integration of artificial intelligence methods (e.g., deep learning) in bioinformatics & computational biology frameworks, leveraging the information of multiple layers such as high-throughput omics and bioimaging data. He is an expert on bioinformatics tools for massive omics data, high-performance computing, and scientific programming in Python and R. A member of the MAQC/SEQC and FANTOM consortiums, Marco co-authored >40 papers in peer-reviewed journals. Further, he runs workshops on bioinformatics and machine learning, and he is involved in teaching activities on statistics, statistical learning, and data visualization at the Data Science M.Sc. at the University of Trento.

Diego Sona

Email: sona@fbk.eu

Diego Sona


Matteo Pozzi

Email: mpozzi@fbk.eu

Matteo Pozzi is a PhD student in Computational Biology working on explainable artificial intelligence (XAI) applied to the healthcare domain. He has a bachelor degree in biology from the university of Parma and a MSc In quantitative and computational biology from the university of Trento in which he worked on the integration of drug's and CRISPR's screening. He is interested in applying machine learning techniques to clinical, omics and imaging data such that the solution can be better understood and trusted by clinicians, biologist and decision makers.

Massimiliano Datres

Email: mdatres@fbk.eu

Massimiliano Datres is a PhD student in Mathematics at FBK and University of Trento. He is currently working on the analytical, stochastic and applicative aspects of Deep Neural Networks with a particular focus on Quantized Neural Networks.

Scientific Developers

Erich Robbi

Email: erobbi@fbk.eu

I'm now pursuing a Master of Science in Data Science at the University of Trento. I am a junior researcher and technologist at the DSH, and I am now involved in a project that relates to digital pathology.

Carlotta Cazzolli

Email: ccazzolli@fbk.eu

Carlotta Cazzolli is a B.Sc student in Computer, Communications and Electronic Engineering at Trento University. She is currently working as a junior scientific programmer in the Data Science for Health unit.

Former Members

Venet Osmani

Email: vosmani@fbk.eu

Venet is a Senior Researcher in e-health group at Fondazione Bruno Kessler research institute and Lecturer in department of Psychology and Cognitive Science at University of Trento, Italy. Previously worked with CREATE-NET research centre. His research interests are in computational modelling of human behaviour as well as modelling disease trajectories from clinical (EHR) data to: estimate risk of developing chronic diseases and predict outcomes in critical care (ICU).

Marco Di Francesco

Email: mdifrancesco@fbk.eu

Marco di Francesco is a B.Sc student in Computer Science at the University of Trento. He has been working at FBK as a Scientific Developer, focusing on the application of Machine Learning where he developed Artificial Intelligence systems applied to the fields of healthcare and environment.