About me: I have a mix of academic background ranging from machine learning, data science to organisational psychology and management sciences. I did my undergraduate degree in Business Management at the University of Sheffield and a master’s in Information Science at University College London where I was particularly focusing on using machine learning/deep learning approaches to solve novel natural language processing problems such as cross-domain sentiment analysis. I spend my leisure time on reading (sci-fi, behavioural sciences mostly), listening to podcasts and playing basketball.
My research: For this PhD, I will be leveraging my knowledge in artificial intelligence and social sciences to uncover secrets in human cognition. More specifically, I will be working on using unsupervised deep learning approaches to build embedding spaces from natural images and try to relate them to neural embedding spaces extracted by fMRI combining with psychological experiments to explore the dimensionality as well as functional differences of the human brain.
The difference my research makes: A successful alignment of object embedding spaces with neural embedding spaces can reveal more insights in terms of how human perception works in our daily life. Research results can be useful in enlightening the creation of computer programmes whose information processing systems are more akin to human cognitions, which could lead to more accurate information/image retrieval and better human-computer interaction in the future. The research methodology itself is also a novel experimentation on combining cross-disciplinary resources and techniques to solve complex problems.
Supervisors: Prof Bradley Love