I am a PhD candidate in Electrical Engineering at Stanford University advised by Prof. Daniel Rubin. My research interests lie in the intersection of machine learning and medicine. I develop machine learning methods for medical applications by leveraging the important characteristics in medical data. I work closely with clinical experts from the Stanford School of Medicine to better understand the clinical needs. Prior to Stanford, I was fortunate to be advised by Prof. Thomas Yeo at National University of Singapore.
PhD in Electrical Engineering, 2018 - Present
BEng in Electrical Engineering (Highest Distinction Honor), 2016
National University of Singapore
We quantify the value of data in a large public chest X-ray dataset using data Shapley values.