Lina graduated first in the 4-year degree of Statistics at the Athens University of Economics and Business. She continued her studies in the same university and received her MSc degree in Statistics in September 2017. In October 2017 she joined the University of Cambridge as a first year PhD student in the Department of Medical Genetics. Her research interests focus on the interface between Bayesian inference and machine learning techniques with the aim to explore the trade-off between computational accuracy and speed in inferential problems involving high-dimensional structured data.
In her PhD research project, Variational Inference (VI) will be used in combination with Markov Chain Monte Carlo (MCMC) sampling algorithms to enable Bayesian inference to meet the demands of the new “big data” era in biology and biomedicine. In particular, off-the-shelf solutions provided by probabilistic programming languages will be compared with crafted learning algorithms that combine variational approximation and MCMC simulation. In summary, during her PhD, Lina aims to introduce hybrid computational strategies to improve the scalability of Bayesian models and to greatly extend their applicability to a wider range of computationally demanding problems arising in biology and biomedicine.