Uncertainty Quantification is a broad term that encompasses several different techniques, from parameter estimation
to uncertainty characterization and model calibration, able to predict the stochastic variations of a quantity of
interest under variable conditions. It is well recognized that quantifying uncertainty is essential for computational
predictions to have any real value. Such indication becomes of paramount importance in the case of biomedical modeling.
In fact, despite major recent advancements, the application of patient-specific modeling in clinical practice still
faces a critical barrier with respect to the variability in the simulation output, arising from different levels of
uncertainty inside a model built from data. The incorrect assumption of perfect knowledge of the subject’s
characteristics can entail questionable choices for instance in surgical planning, potentially leading to treatment
failure. In general, primary sources of uncertainties may result from input variability (aleatory/irreducible
uncertainty), such as anatomical definition, tissue characteristics (like elasticity or excitability) and unknown
boundary conditions, or from a lack of knowledge (epistemic/reducible uncertainty), like modeling assumptions or the
influence of yet unknown physical phenomena. Additional uncertainty can also arise at the simulation stage.
The school is part of the RICAM Special Semester on Mathematical methods in Medicine, and will offer complementary
training on UQ techniques with applications in state-of-the-art problems of biomedical research, from medical imaging,
passing through experimental test cases, and addressing the computational modeling of bones, cornea, heart and gut.
Lecturers will be renowned expert scientists from multidisciplinary fields. The school is intended for Master/PhD
students and early career researchers, and aims at creating optimal conditions for future synergic and multidisciplinary
cooperation. Two social and cultural activities will be organized where students will meet lecturers in an informal
Anna Pandolfi (Politecnico di Milano IT): CO
Anna Pandolfi is Full Professor of Solid and Structural Mechanics at Politecnico di Milano. She is an expert in
computational biomechanics for soft fiber-reinforced tissues with a special focus on cornea modeling and health
Flavio H. Fenton (Georgia Tech USA): C2
Flavio H. Fenton is Professor of Physics at the School of Physics, Georgia Institute of Technology (USA). His
expertise covers a wide range of studies on experimental, theoretical and numerical cardiac dynamics.
Seth H. Weinberg (The Ohio State University): C1
Seth H. Weinberg is Associate Professor of Biomedical Engineering at the College of Engineering, Ohio State
University (USA). His research focuses on mathematical and computational modeling of cardiac physiology.
Vijay Rajagopal (The University of Monash): C3
Vijay Rajagopal is Associate Professor of Computational Cellular Biomechanics at the University of Melbourne
(AUS). His research aims at creating anatomically and physiologically realistic computational models for
clinical and pharmaceutical translation.
Zohar Yosibash (Tel Aviv University): M + B (canceled)
Sebastian Brandstäter (University of the Bundeswehr Munich): GSA global sensitivity analysis
Sebastian Brandstäter is Postdoctoral Researcher at the Institute for Mathematics and Computer-Based Simulation,
University of the Bundeswehr Munich, Germany.
Peng Du (Auckland Bioengineering Institute): G
Peng Du is Associate Professor at the Faculty of Engineering, Engineering Science and at the Bioengineering Institute,
University of Auckland (NZ). His research covers the applications of computational physiology, instrumentation, and
experimental physiology in the gastrointestinal tract.
Emiliano Schena (Campus Bio-Medico of Rome): E
Emiliano Schena is Full Professor of Measurements and Biomedical Instrumentation at the Faculty of Engineering,
University of Rome “Campus Bio-Medico”. His research interests are focused on the study of biological tissue thermal
treatment, experimental estimation of tissue optical properties using innovative measurement techniques.