Daniel de Vassimon Manela
DPhil in Statistics student
I am a first year DPhil student interested in applications of causal inference to the biomedical/clinical spaces and am supervised by Robin Evans. Before starting at Oxford, I worked in the pharmaceutical space and worked on developing ML methods to address problems in the clinical spaces. Even earlier to that, I completed degrees in Physical Natural Sciences and Computational Statistics/ML from the University of Cambridge and UCL, respectively.
I am interested in developing machine learning methods and specifically causal inference techniques to address challenges in clinical and medical spaces. Recent explosion of clinical data lead to a variety of attempts to draw meaningful treatment inferences from observational data. However, naive applications of non-causal methods can lead to biased findings, which could have critical impacts on patients.
My research seeks to address these challenges and learn unbiased effects from both observational and randomised trial data. Of particular interest is the challenging case when learning from data with unobserved confounders.