Dr Tingting Zhu
Dr Tingting Zhu's current research focuses on machine learning for global health, with specific emphasis on chronic diseases. Her research investigates how statistical methods can be used for understanding complex patient data acquired from low-cost devices in a resource-constrained setting. Tingting has also previously developed algorithms for online, unsupervised learning that utilises crowd-sourced medical data.
As a senior researcher in the Computational Health Informatics Lab at the Institute of Biomedical Engineering led by Professor David Clifton, Tingting’s work involves investigating the development of Bayesian methods for phenotyping patients, with a special emphasis on haemodialysis studies in collaboration with Prof. Chris Pugh of the Nuffield Department of Medicine. This research is funded by the National Institute for Health Research and the Engineering and Physical Sciences Research Council.
Given Tingting's interest in global health, she is currently the principal investigator (PI) for a project that looks to improving access to high-quality health care in the Philippines, where the doctor:patient ratios are 1:20,000, through low-cost medical devices using machine-learning techniques. This project is in collaboration with the National Health Centre, Philippines and supported by the Royal Academy of Engineering Frontiers of Engineering for Development Award.
Tingting has also been awarded an EPSRC NetworksPlus prize as a PI to work on the next generation of mhealth applications with clinicians in Guangzhou (including overseeing a proof-of-principle study of 20,000 patients in one of China’s leading cardiovascular hospitals), working with the George Institute for Global Health.