I am a Lecturer in Statistics in the Department of
Mathematics in Imperial College London, where I am teaching advanced
statistical modelling, graphical modelling, and official statistics. My research
lies with computational statistics, with a particular focus on streaming data
analysis. My theoretical interests include stochastic
approximation, graphical modelling, variable selection and online non-parametric methods.
I am interested in pursuing
innovations in streaming and big data analysis, including network analytics (data mining
on graphs, anomalous behaviour in social networks, learning in multi-agent games),
business intelligence applications (energy consumption forecasting, recommender
systems, online personalised advertising), retail banking (automatic fraud
detection, drifting credit risk tracking), and cybersecurity. I am also interested in official statistics and open data. I am the co-founder and Chief Data Scientist of London start-up Mentat Innovations.
Short Bio. I graduated with a BAHons in
Mathematics from Pembroke College, Cambridge University in 2003, and then obtained an MSc in Learning from Data
from the Informatics School of Edinburgh University, as well as an
MSc in Logic and Algorithms from the University of Athens. I
completed my PhD in the Institute for Mathematical
Sciences at Imperial College London, entitled 'A statistical framework for
streaming data analysis' and then worked as a Research Fellow at the Statistical Laboratory in Cambridge University.
I have so far been involved in private consultancy in the security industry, and