Within months of joining the PhD programme, Haoting was making a contribution to his field, collaborating with fellow student Fabian Falck to publish an academic paper on machine learning.
HDRUK-Turing Wellcome PhDs are four years, with an foundation year that is designed to immerse students in the world of health data science, learn where their interests and abilities lie, and spend time preparing for their three-year thesis project
Haoting says: “This was really helpful. Compared to a normal three-year PhD, where you get straight into PhD thesis at the very first day, we had a year to explore and understand different things.
“So we were able to understand what are the challenges in health data science, which are quite difficult for people to see from the outside. And then we had time to look for the ideal PhD thesis that we would like to do.
“It was really good to be able to do this in a relaxed environment. In a normal PhD application it’s very intense and you may not even be 100% sure if you and your supervisor are suitable fit.
“But in this programme Chris Yau, the Director, introduced me to academics in the machine learning group of the computer science department at Cambridge and we found that they had a project on drug discovery, which I’m interested in. It turned out that we are a natural fit.”
Haoting’s research, which is in collaboration with AstraZeneca, is into active learning and the optimisation of drug combinations and aims to bring real-world healthcare benefits.
While it is still early days, he intends to pursue a career in machine learning and health data science either as an academic researcher or in industry.
A first degree was in Mathematics and Statistics at the University of Oxford was followed by a Master’s in Machine Learning at University College London (UCL).
Outside his research studies Haoting enjoys reading and jogging and is a fan of motorsport, especially Formula One, who occasionally does some Go Karting.