Yin-Cong Zhi

Yin-Cong is a postdoctoral researcher in machine learning for infectious diseases, part of Oxford Population Health at the Big Data Institute, and a member of the Chami Group working on the SchistoTrack project. 

The group works on all-aspect studies relating to Schistosomiasis in Uganda. Yin-Cong's focus is on providing a Bayesian perspective to modelling multi-morbidities in patients, to understand the broad spectrum of morbidities that schistosomiasis can cause and how they affect each other. In addition, he is looking to apply graph-based machine learning to model the disease progression using the data collected by our Ugandan team. 

Prior to joining this, Yin-Cong completed his DPhil in Machine Learning at the University of Oxford. His thesis looked into developing Gaussian processes for graph data, to expand on the literature of Bayesian methods for learning on graphs as opposed to the common graph neural networks. The tools used included kernel methods, Bayesian inference, multi-scale modelling, and in particular graph signal processing to study modelling from a spectral domain perspective.

Outside work, Yin-Cong has a lifelong hobby of making origami, and enjoys watching and playing football.