Mauro Gasparini

Mauro Gasparini is a Full Professor at the Department of Mathematical Sciences (DISMA) of Polytechnic University of Turin. He serves as Director of DISMA since 2019, Member of Academic Senate, and co-leader in the SmartData@PoliTO Big Data Laboratory. His career spans academia and industry, including roles at Purdue University (Assistant Professor 1992-1996) and Novartis (Senior Statistician 1996-1998). He has been Editor of Biometrical Journal (2012-2015) and maintains referee activities across international journals.

• PhD from University of Michigan (1992, Dirichlet process applications)
• Academic leadership: Department Director, Editorial boards, ISTAT Advisor
• Research spans Bayesian methodology with biomedical applications
• Maintains collaborations with Novartis, Chiesi, and research centers

His research interests focus on Bayesian inference, Biostatistics, and Clinical trials methodology, particularly addressing issues in pharmaceutical development, genomic data analysis, and medical decision-making. Recent work includes vaccine efficacy modeling, optimal imaging timing for cancer diagnostics, and adaptive trial designs.

Key publication trends show interdisciplinary applications in Statistics in Medicine, Biometrics, and Statistical Methods in Medical Research, with emphasis on biomedical data science, Bayesian adaptive methods, and clinical decision support systems.

Scientific contributions include:

• Editor, Biometrical Journal (2012-2015)
• Advisor, Italian National Institute of Statistics (2020-2024)
• Leadership in multiple research projects (NODES, SORGENTE, IDEAS)

As PhD advisor, he supervises students in:

• Shaoshi Tang (Clinical trial modeling)
• Saeed Sani (Biomedical data analysis)
• Marco Ratta (Genomic statistics)
• Luca Rondano (Bayesian methods)
• Vittorio Zampinetti (Tumor DNA sequencing)
• Fulvio Di Stefano (Evidence-based decision statistical methods)

He leads research projects in pharmaceutical statistics, genomic surveillance, and spatial risk assessment frameworks, with recent emphasis on SARS-CoV-2 analysis and cancer progression modeling.