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About Me
I am a postgraduate researcher in statistics working at the boundary of computer science as part of the Oxford-Warwick Statistics Programme (OxWaSP) together with Theodoros Damoulas and Chenlei Leng. I am also part of the Warwick Machine Learning Group, a visiting researcher at the Alan Turing Institute and a Facebook Fellow.
My research interests are focused on scalable spatio-temporal inference procedures for data generating mechanisms in high dimensions that are ill-behaved or difficult to describe. This encompasses modelling and doing inference for non-stationary data streams that may have changing behaviours across time as well as space. The algorithms and inferential procedures developed as part of this research will be used within the framework of the Clean Air London project at the Turing Institute to support London's Major's office in taking well-informed and data-driven policy decisions. For a more detailed look, here is my CV.
Research Interests

Modelling changepoints in a Bayesian way is elegant and computationally efficient (see Adams & MacKay, 2007; Fearnhead & Liu, 2005). I am working to extend this into a spatio-temporal context and to enable scalable robust inference on multivariate data.

When dealing with on-line large scale data streams in a Bayesian way, scalable inference methods are key. In particular, apart from being slow at run time, sampling-based approaches also require a memory-consuming particle-based representation of the distributions in question. At the other end of the spectrum, standard variational inference methods are fast, but provide insufficient uncertainty quantification in noisy, ill-behaved data streams. To remedy this issue, I have recently developed a generalization of variational inference methods that allows for customized uncertainty quantification that is as conservative and robust as the application in question requires it to be.

Selected Presentations
Reviewing Activities

NeurIPS 2019

Software

I have written a substantial amount of software in Python accompanying my research, through which we have been nominated as Turing Reproducible Research Champions 2018 by the Alan Turing Institute.