Cristian Minoccheri

Research Investigator, Computational Medicine and Bioinformatics

Computational medicine, interpretable machine learning, tensor methods

Dr. Minoccheri’s research interests focus on using mathematical tools to enhance existing machine learning methods and develop novel ones. A central topic is the use of tensor methods, multilinear algebra, and invariant theory to leverage higher order structural properties in data mining, classification, and deep learning. Other research interests include interpretable machine learning and transparent models. The main applications are in the computational medicine domain, such as phenotyping, medical image segmentation, drug design, patients’ prognosis.