Applications:
Laboratory Experimentation: Chemistry, Synthetic Biology
Customer Experimentation: A/B testing, market modeling
Research & Methods: I specialise in
Causal Inference:
Partial Identification
Synthetic Control
Intervention Generalisation
Bayesian Optimisation (Active Learning)
Causal Bayesian Optimisation
Multi-fidelity Bayesian Optimisation
Transfer-learning Bayesian Optimisation
Big Maths and I
Give me anonymous feedback via Admonymous here.
Research:
Kaichuang (Kevin) Yang, University of Oxford, MSc -> KAUST, PhD
Dylan Schubert, UCL, MSc -> Chubb Global Markets
Jakub Kmec, UCL, MSc -> InstaDeep
Christophe Muller, Oxford, PhD -> TBD
Kyra Edwards, Oxford, PhD -> TBD
Johannes Hruza, Copenhagen, PhD -> TBD
Julia Zervakos, UCL, MSc -> TBD
Ewan Burns, UCL, MSc -> TBD
Nigel Cendra, UCL, MSc -> TBD
Thesis/Transfer Committees:
Vuyiswa Kubulasa, University of Cape Town, MSc
Ruizi Yan, University of Oxford, PhD
2025+ Pioneer Fellow, University of Oxford, UK
Part of the Robin Evans Group, researching Causal Inference, Bayesian Optimisation and its combinations.
2024 PhD University College London, UK
Advised by Ricardo Silva on Fundamentals of Causal Inference
2019 PhD/MSc Syracuse University, US
Advised by Chilukuri Mohan and Volker Weiss, transferred to UCL
2017 BA University of Exeter, UK
Studied Philosophy, Politics and Economics with a focus on Statistics, Machine Learning and the Philosophy of Science
Non-parametric identifiability and sensitivity analysis of synthetic control models
J Zeitler, A Vlontzos, CM Gilligan-Lee
Stochastic causal programming for bounding treatment effects
K Padh, J Zeitler, D Watson, M Kusner, R Silva, N Kilbertus
Intervention Generalization: A View from Factor Graph Models
R Silva, G Bravo-Hermsdorff, D Watson, J Yu, J Zeitler
Systems and methods for bias bounded sensitivity analysis of synthetic control models (Google patents)
Language Learning with Lyrics (link)
r-Transfer Learning Bayesian Optimisation (link)