Portrait of Ivo Dinov
Methodologies: Complex time (kime), Computational processing, Mathematical modeling, Predictive health analytics, Scientific visualization of Big Data, Spacekime theory, Statistical analysis

Ivo Dinov

Professor, Health Behavior and Biological Sciences


Computational Medicine and Bioinformatics
Michigan Institute for Data Science (MIDAS)

Mathematical representations of big data, spacekime analytics, computational statistics, , longitudinal morphometric studies of development (e.g., Autism, Schizophrenia), maturation (e.g., depression, pain) and aging (e.g., Alzheimer’s disease, Parkinson’s disease). Developing, validating, and disseminating novel methods (e.g., spacekime analytics) and technologies (e.g., CBDA, DataSifter, TCIU) for mathematical modeling, statistical computing, biomedical applications, scientific education, and active learning.

Understanding cognitive function, modeling neuro-connectivity, analyzing multi-source, heterogeneous, incomplete, time-varying and complex brain data require advanced mathematical techniques, modern spacekime analytics, powerful statistical computing algorithms, and cutting-edge artificial intelligence tools.