Embedded Files
Email: ssafo@umn.edu Phone: 612-625-9142 ORCID GitHub Multiview Dashboard CV
Welcome!
I am an Associate Professor in the Division of Biostatistics and Health Data Science and a Graduate Faculty of Data Science in the College of Science and Engineering at the University of Minnesota. I am interested in developing robust, explainable, and usable statistical and machine learning methods (e.g. classification, discriminant analysis, clustering, dimension reduction, sample size estimation, deep learning) and algorithms for high dimensional data to advance clinical translational research and precision medicine. Some current interests include functional data analysis and social determinants of health.
My methods research is currently supported by multiple PI grants including: Maximizing Investigators Research Award (MIRA, R35 from NIGMS) for early stage investigators, Administrative Supplements from NIA and the Office of Data Science and Strategy, and a UMN internal grant.
Education
Ph.D., Statistics, The University of Georgia, 2014
MSc., Applied Mathematics, The University of Akron, 2009
BA., Mathematics and Economics, University of Ghana, 2006
Research Interests
Statistical Methods
Multivariate Statistical Analysis
Integrative Analysis of Multiple High Dimensional Data
Statistical Learning (Discriminant Analysis, Classification, Clustering)
Sample Size Estimation for High Dimensional Data
Functional Data Analysis
Deep Learning
Applied
Cardiovascular Diseases; HIV; Diabetes; COPD; COVID-19
Genetic Epidemiology
Metabolomics
Honors, Awards, Membership
University of Minnesota McKnight Land-Grant Professor, 2023-2025
Standing Member, NIH Analytics and Statistics for Population Research Panel A – ASPA, 2022-2026
NIH ESI Outstanding Award, 2021-2026
Elected Member, International Statistical Institute (ISI), 2022
University of Minnesota CTSI KL2 Scholar, 2018-2021
Emory University BIRCWH Scholar, 2016-2017
PRIDE Cardiovascular Genetics Epidemiology Scholar, Washington University, St Louis, 2016-2018
Google Sites
Report abuse