Imperial College London


Faculty of Natural SciencesDepartment of Mathematics

Honorary Lecturer



x.miscouridou Website




Huxley BuildingSouth Kensington Campus





I am a Lecturer in Statistics in the Department of Mathematics at Imperial College London and also a member of the Imperial-X initiative in machine learning, artificial intelligence and data science. 

My main research interests are in the broad area of Bayesian statistical machine learning aiming to build methods that combine the strengths of statistics and computation aspiring to answer scientific questions with real life impact. 

My research focuses on statistical network/graph modelling, Bayesian Nonparametrics, stochastic process modelling and deep generative models.

I also enjoy working in other areas of deep learning, infectious disease modelling, Covid-19 research, branching processes. 

I am interested in new PhD students. If you find my research area interesting don't hesitate to contact me.



Todeschini A, Miscouridou X, Caron F, 2020, Exchangeable random measures for sparse and modular graphs with overlapping communities, Journal of the Royal Statistical Society: Series B (statistical Methodology), Vol:82, ISSN:1369-7412, Pages:487-520


Miscouridou X, Modelling sparsity, heterogeneity, reciprocity and community structure in temporal interaction data, Neural Information Processing Systems

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