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.