Methodologies: Data, Statistics and Stochastic Methods, Education, Visualization Relevant Projects:

Center for Complexity and Self-management of Chronic Disease (CSCD) University of Michigan Udall Center for Excellence in Parkinson’s Disease University of Michigan Nutrition Obesity Research Center (MNORC)


Big Data to Knowledge (

Probability Distributome (

Statistics Online Computational Resource (

Ivo Dinov

Associate Professor, Nursing


Statistics Online Computational Resource (SOCR), Michigan Institute for Data Science (MIDAS), Computational Medicine and Bioinformatics, Center for Network and Storage-Enabled Collaborative Computational Science

Dr. Ivo Dinov directs the Statistics Online Computational Resource (SOCR), co-directs the multi-institutional Probability Distributome Project, and is an associate director for education of the Michigan Institute for Data Science (MIDAS).

Dr. Dinov is an expert in mathematical modeling, statistical analysis, computational processing and visualization of Big Data. He is involved in longitudinal morphometric studies of human development (e.g., Autism, Schizophrenia), maturation (e.g., depression, pain) and aging (e.g., Alzheimer’s and Parkinson’s diseases). Dr. Dinov is developing, validating and disseminating novel technology-enhanced pedagogical approaches for scientific education and active learning.



Analyzing Big observational data including thousands of Parkinson’s disease patients based on tens-of-thousands signature biomarkers derived from multi-source imaging, genetics, clinical, physiologic, phenomics and demographic data elements is challenging. We are developing Big Data representation strategies, implementing efficient algorithms and introducing software tools for managing, analyzing, modeling and visualizing large, complex, incongruent and heterogeneous data. Such service-oriented platforms and methodological advances enable Big Data Discovery Science and present existing opportunities for learners, educators, researchers, practitioners and policy makers.