Douglas Spencer completed an MSc in Mathematical Sciences at the University of Oxford, following a BSc in Computer Science and Mathematics at The University of Manchester.
His master’s project, supervised by Prof Patrick Rebeschini, explored the use of conformal martingales to construct anytime-valid prediction sets for black-box machine learning models. Previously, he worked on uncertainty quantification for quantum machine learning under non-stationary noise, leading to work published in TMLR.
At StatML, Douglas is excited to continue research into the theory of uncertainty and risk control for sequential prediction and adaptive model deployment.
Outside of his studies, Douglas enjoys sports, particularly rock climbing, as well as socialising and reading.
