Jeremias Knoblauch

Jeremias Knoblauch

Assistant Professor and EPSRC Fellow in Machine Learning & Statistics

University College London (UCL)

Biography

I am currently Assistant Professor/Lecturer at UCL’s Department of Statistical Science. Until 07/2025, I am fully bought out of teaching and administrative duties with an EPSRC research fellowship to continue my work on Optimisation-centric Generalisations of Bayesian Inference. I am also a visiting researcher at the Alan Turing Institute’s Data-Centric Engineering Programme, as well as an advisor for HopStair and Idoven.

My research revolves around extending the paradigm of Bayesian inference to cope with the challenges posed by modern large-scale data, simulator models, and machine learning techniques. In this context, I am particularly interested in generalised Bayesian inference, model misspecification and robustification strategies, computational challenges involving intractability, and variational methods. If you would like to learn more about my research, I have summarised some of my key contributions in the following talk.

Prior to that, I was a Biometrika Fellow in 2021/2022, also based at UCL. Before that, I was a doctoral candidate within the Oxford-Warwick Statistics programme (2016-2021) as well as the first UK-based Facebook Fellow (2020/2021). During that time, I also worked with the research arms of Amazon (2019) and DeepMind (2021). I remain eager to stay in close contact with industry, and am very open to being approached by potential industrial partners for both academic and non-academic work.

Download my (very likely outdated) resumé.

Interests
  • Generalised & Post-Bayesian methodology
  • Robust Bayesian inference
  • Variational Methods
Education
  • PhD in Statistical Sciences, 2022

    OxWaSP (Oxford-Warwick Statistics Programme)

  • BSc+MSc in Econometrics & Operations Research, 2016

    Maastricht University

Publications

The below list is likely incomplete; my google scholar page is more up to date.