AI4Nof1
Reinforcement learning for management of chronic conditions
Reducing patient burden and research cost: the AI4Nof1 project leverages cutting edge developments in (causal, neurosymbolic) reinforcement learning, psychometrics and digital epidemiology to build adaptive personalised treatment regimes for chronic conditions, simultaneously identifying phenotypes and causal pathways while minimising the time and number of measurements needed for patients to find a treatment that is right for them.
The project combines active learning and Bayesian modelling with mobile health technology to facilitate simultaneous tailoring of treatments and discovery of population-level knowledge.
Sebastian Vollmer
Professor for Applications of Machine Learning
My research interests lie at the interface of applied probability, statistical inference and machine learning.