Zhangdaihong (Jessie) Liu undertook her PhD at the Mathematics for Real-World Systems CDT at University of Warwick. During this time, she was also a visiting PhD student at the Big Data Institute, University of Oxford, and a PhD enrichment student at the Alan Turing Institute. Prior to this, she obtained an MSc in Mathematics of Systems from Warwick University, an MSc in Mathematical Finance at Loughborough University, and a BSc in Mathematics at Shandong University, China.
Her PhD thesis entitled ‘Latent Variable Modelling of Population Neuroimaging and Behavioural Data’ focused on the development of a dimension reduction method that improves the interpretability of latent variable models applied to health-related datasets. Her research also involved uncovering latent patterns between neuroimaging, behavioural and demographic measures, as well as the application of various large dataset processing techniques.
Jessie’s research interests also include predictive modelling, feature extractions, recommender systems, deep learning and reproducible research
- Predictive modelling
- Feature extractions
- Recommender systems
- Deep learning
- Reproducible research
Jessie is using a large-scale, freely-available relational database of intensive care patients to stratify heart failure patients to understand and improve prediction accuracy. She is also working on the validation of a model developed at Oxford for severity prediction in Covid-19 patients using data from hospitals in Wuhan, China.