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.
Cristian Minoccheri
Research Investigator, Computational Medicine and Bioinformatics, Medical School
Computational medicine, interpretable machine learning, tensor methods
COntact
Location
Ann Arbor
Methodologies
Data Mining / Graph-Based Methods and Networks / Machine Learning
Applications