Personal profile


Daniel studies mood, learning, and decision making. He uses computational methods (e.g., reinforcement learning models of behaviour, multivariate pattern analysis of neural data) to understand how these phenomena interact. He is particularly interested in investigating the ways that interactions between mood, learning, and decision making might go awry in psychiatric conditions like major depression and bipolar disorder.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Education/Academic qualification

Psychology, PhD, Belief updating and information seeking in decision making under uncertainty, University of Melbourne

Award Date: 5 Apr 2017

Research area keywords

  • mood
  • mood disorders
  • Affective science
  • learning
  • decision making
  • Computational Modelling
  • gambling

Collaborations and top research areas from the last five years

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