I am interested in developing statistical and neurally-inspired models of learning, and examining how the structure of environmental input affects computational models’ efficiency. I chose this specific field of study for several reasons. First, I am intrigued by the relationship between machine learning and human cognition. In particular, visualizing and characterizing various learning and decision processes. And I am also fascinated by how the neural network approach based on reinforcement and prediction learning might reflect the brain’s computational principle underlying flexible and adaptive behaviours. Eventually, I hope I can build flexible and efficient artificial intelligence with the knowledge of human cognition that can be used in both research and applied areas .