Hi I’m Steph and my research question tackles human mental representation of causes and explanations. We build models of how people explain surprising behaviour, using unobserved variables, counterfactual simulation and Bayesian inference. I use JavaScript to run my experiments and R to visualise and present my work.

Before reentering higher education in 2017 I worked as a financial analyst and chartered accountant, which gives me extensive business and financial acumen and confidence presenting to investors and directors. My PhD is run and funded by the Natural Language Processing Centre for Doctoral Training September 2021 to August 2025, which has given me broad skills in language modelling and other current issues in machine learning and data science.

I have been interested questions of meaning ever since coming into contact with abstract art and semiotics in my undergraduate degree. Learning to speak and write in Russian let me see the complex relationship between language and thought. This varied background lets me take a considered stance on many of the wider methodological and scientific issues in psychology and philosophy.

I aim to unify these diverse strands into data science for strategy or healthcare economics. My ongoing dream is an app that helps people choose better healthcare interventions: a ‘reasoning tool for normal people’. To this end I’m looking for either a technical cofounder or a PI for a 2-year project to translate my relatively small PhD causal models to a healthtech setting; please get in touch if that’s you!