Skip to main content

Jeremias Knoblauch

Click here for my personal webpage
About Me
I am a 2nd year 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. My 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 For a more detailed look, here is my (outdated) CV.
Research Interests

Modelling changepoints in a Bayesian way is elegant and computationally efficient. I am currently working to extend this into a spatio-temporal context and to enable scalable robust inference on multivariate data.

Recent & Upcoming Talks
Recent & Upcoming Talks by Collaborators

My friend and collaborator Jack Jewson will be presenting novel robust Bayesian techniques for streaming data which we recently started developing together:


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. As soon as it is failsafe, the software will be made publicly available.


Office: C1.02, Zeeman building


Personal webpage: