My research intersts lie in the broad area of statistical machine learning with broader goal to build methods that combine the strengths of statistics and computation aspiring to answer scientific questions with impact in real life.
My phd focus was on Bayesian non parametric modelling for random graphs, complex networks, time interaction data and on practical Bayesian non parametric methods and theory for a variety of applications.
My research to date includes more broadly Bayesian methods, deep generative models, unsupervised learning techniques, point processes and stochastic processes with applications in social science, epidemiology and finance.
I am supervising Iwona Hawlyruk on her PhD on Bayesian Statistics and Machine Learning methods applied in Epidemiology.
If you are interested in a PhD at Imperial working with me, feel free to send me an email to discuss this. See also the PhD studentships at Imperial and two EPSRC CDTs joint with the University of Oxford: StatML-Modern Statistics and Statistical Machine Learning and Mathematics of Random Systems: Analysis, Models and Algorithms.
x [dot] miscouridou [at] imperial [dot] ac [dot] uk