Rate My Professor Sollie Millard

His research specializations include data science, analytics, statistics, mixture models, semi-parametric generalised linear models, EM-type algorithms for non-parametric regressions, Bayesian nonparametric estimation of differential entropy, and shrinkage estimators for big data analytics. With 26 publications and over 270 citations, key contributions feature "Bayesian nonparametric estimation of differential entropy for toroidal data" (2025, with N. Nakhaei Rad et al.), "A modified EM-type algorithm to estimate semi-parametric mixtures of non-parametric regressions" (2024, with S.B. Skhosana and F.H.J. Kanfer), "Efficient Estimation and Validation of Shrinkage Estimators in Big Data Analytics" (2023, with S. du Plessis et al.), "Understanding Opportunity Evaluation Prototypes in Search of more Entrepreneurs" (2023, with M. Pretorius and I. Le Roux), "A Novel EM-Type Algorithm to Estimate Semi-Parametric Mixtures of Partially Linear Models" (2023, with S.B. Skhosana and F.H.J. Kanfer), "Fitting Non-Parametric Mixture of Regressions: Introducing an EM-Type Algorithm to Address the Label-Switching Problem" (2022, with S.B. Skhosana and F.H.J. Kanfer), and "Mixtures of Semi-Parametric Generalised Linear Models" (2022). As Co-Principal Investigator and Senior Researcher, he contributed to the Global Volunteer Index for the United Nations Volunteers' State of the World's Volunteerism Report.