Dr Yul HR Kang

Queen Mary University of London

Yul  Kang, MD, PhD is a computational cognitive neuroscientist studying how  natural & artificial neural networks handle unavoidable uncertainty  in sequential decision-making, such as wayfinding during navigation.

He uses Bayesian approaches and probabilistic neural representation  models, with applications to games, fundamental science, and healthcare.

He received his MD in Seoul National University (South Korea), PhD in  Columbia University (USA), and did postdoctoral research at the  University of Cambridge (UK), where he was elected and served as a  Junior Research Fellow.

His work was published in top-tier journals such as Current Biology  and eLife, and was presented as a talk in leading computational  neuroscience conferences such as Cosyne and Bernstein Conference. His  work was featured in news outlets such as The Independent.

His research addresses how the brain handles unavoidable uncertainty  (e.g., from ambiguous visual scene) during sequential decision-making  (e.g., wayfinding). It helps understand players’ behaviour and predict  their uncertainty given a map (and hence difficulty). Since neurological  patients often show specific impairments in such tasks, it may help  earlier and more specific diagnosis of diseases.

Yul is interested in predicting players’ behaviour, procedural  generation of levels by predicting subjective uncertainty and fun, and  using games for diagnosis of psychiatric and neurological diseases.