MD, PhD (Cantab)
- Wellcome Trust Named Research Associate
Dr Fei-Yang Huang earned his PhD in Neurophysiology from the University of Cambridge (Queens' College) and his MD from National Taiwan University with a minor degree in Economics. He combines behavioural theories, neurophysiology recording, and computational modelling to uncover how the brain performs complex cognitive functions, in particular learning and decision-making.
His current research focuses on how the brain processes nutrient information to make food choices. In particular, he studies behavioural and neuronal mechanisms underlying food choices by training animals to choose from nutrient-defined food options in controlled laboratory setting and record single-neuron activities during decision-making. He takes an interdisciplinary approach, using decision theories in economics, psychology, ecology, and machine learning methods, to formalise decisions observed in animals and to uncover decision computation in single neurons and neural populations. This approach has started to elucidate how neural reward processing is structured by biological critical nutrient components of food rewards. By linking biological decision mechanisms to primate evolution, he asks not just 'how' could primates control nutrient intake, but 'why' our brain is organised for this purpose. Importantly, understanding biological reward mechanisms could make next-generation AI systems stronger and safer by endowing AI value functions with biological and human values.
Nutrient-sensitive reinforcement learning in monkeys.
Huang 黃飛揚 F-Y. and Grabenhorst F., (2023), J Neurosci
Preferences for nutrients and sensory food qualities identify biological sources of economic values in monkeys.
Huang F-Y. et al, (2021), Proc Natl Acad Sci U S A, 118
Nutrient-sensitive reinforcement learning in monkeys
Huang F-Y. and Grabenhorst F., (2021)