About
Edisy Chan is a doctoral researcher in the Vision, Learning and Control Research Group within the School of Electronics and Computer Science. His research lies at the intersection of theoretical machine learning, optimisation, and algebraic and geometric methods for data analysis. His work focuses on developing mathematically grounded approaches to uncovering and exploiting structure in data, drawing on a range of techniques including low-rank and matrix factorisation methods. He also has an interest in AI education.
His PhD supervisors are Dr Andersen Ang and Professor Adam Prugel-Bennett.