I’m interested in machine learning and statistics more broadly, particularly Bayesian. Currently, I’m on the StatML programme at the University of Oxford, working with Tom Rainforth and Yee Whye Teh.

Before joining the StatML CDT, I spent four years in quant finance – first in quantitative equity research at UBS and later in cross-asset systematic trading strategies structuring at Goldman Sachs.

I’m passionate about the rigorous use of statistics and machine learning in applied settings. Specifically, I firmly believe it is crucial to 1) incorporate domain knowledge when training data-driven models; 2) thoroughly evaluate these models against suitable baselines; and 3) properly interpret the results of statistical analyses.

For more about my work, see my talks and publications. I’m very happy to collaborate and/or give a talk.