Ivona V.

At Frame, we are leading and overseeing the planning and execution of statistical analysis and data science operations across the main business domains. Supporting business development by providing data-driven solutions spanning a variety of machine learning techniques.

Supporting businesses by providing data driven solutions and data analytics services. Consulting on all stages of development – from survey design and interactive data visualisation to building predictive models using historic data. Ongoing and completed contracts span a wide range of industries including financial, fish farming, third sector, fitness and health, advertising, and PR.

I have been awarded the Maclaurin Scholarship at the University of Glasgow, which consists of part-time PhD studies and part-time lecturing. My research interests include machine learning, Bayesian statistical modeling and predictive modeling. The focus of my PhD studies is hierarchical mixture of experts (HME) models. I am working on the implementation of Bayesian inference for the HME models in C++. The latter includes some well known Markov Chain Monte Carlo (MCMC) methods as well as some novel approaches to be revealed over the course of my PhD. As a course lecturer, I fully engage in planning and delivering the highest standard of education. I am currently lecturing multivariate probability theory and R programming within the School of Mathematics and Statistics. I am experienced in both face-to-face and online teaching. This includes content development, feedback and assessment planning as well as supporting and managing small-group teaching.