The Global Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. Yinghui's work contributes towards the following SDG(s):
About Yinghui
My primary research interest is in developing statistical methodology and the substantive applications to medicine, clinical trials, observational studies and evidence synthesis, as well as using data to improve population health and health care services.
I have experience in conducting big data enabled health research using NHS data, national registry databases, and large and complex data (from up to 24 million people) from national linked electronic health records and longitudinal cohort studies within Trusted Research Environments/Secure Data Environments.
I have a sustained research contribution to developing novel statistical methods in medicine, as well as applied health data science, through disciplinary and interdisciplinary collaborations, supported by external research funding.
I led an impact case study "Improved health research and practice through advancing statistical methods and applications" for REF2021 UoA10 Mathematical Sciences.
I was a Statistical Editor for Cochrane developmental psychosocial and learning problems review group (2011-2023). I sit on Royal Society's International Exchanges Committee and on Royal Statistical Society President Nominating Committee. I am a member of the Executive Group for Health Data Research UK South-West.
Supervised Research Degrees
- Dr Nicole Thomas (2022) Investigation of the effectiveness of an intervention to prevent oral disease in a highly vulnerable child population (co-supervisor)
- Dr Jagriti Sethi (2022) Graphene based biosensors for detection of blood biomarkers of Alzheimer's disease (co-supervisor)
- Dr Lexy Sorrell (2021) Statistical inference about bivariate semi-competing risk data using copulas (Director of Studies)
- Dr Zainab Al-Kaabawi (2018) Bayesian Hierarchical Models for Linear Networks (Director of Studies)
Current PhD Students at University of Plymouth:
- M. Howe: A probabilistic dental treatment risk index (co-supervisor)
- L. Zhang: Bayesian multi-level survival models (Director of Studies)
- S. Riley: Using big data to develop and validate clinical prediction models for survival outcomes following kidney transplant (Director of Studies)
- K. Jagoda: Statistical methods in electronic health records research (Director of Studies)
- L. Ellaway: Enhancing Understanding of long COVID using novel mathematical clustering techniques (co-supervisor)
- M. Dogan: Biosensors for detection of Alzheimer disease biomarkers (co-supervisor)
- S. Nazir: Graphene biosensors for clinical applications in the detection of body fluid AD biomarkers (co-supervisor)
- J. Mnyambo: Prediction of Diagnostic Accuracy using Artificial Intelligence and Big Data Analytics from HeroRats for Tuberculosis Detection (co-supervisor)
Visiting PhD Students:
- Q. Zhang: (Overseas supervisor, Yunnan University), visiting 2022 -2024
- B. Duan: (Overseas supervisor, Yunnan University and Chinese Academy of Sciences), visiting 2022 - 2024
- J. Li: Survival analysis (Overseas supervisor, Yunnan University), visiting 2021 - 2022
- Y. Zhou: Spatial-temporal modelling (Overseas supervisor, Yunnan University), visiting 2021 - 2022
Teaching
I lead the MSc Health Data Science and Statistics programme.
I supervise MSc projects in Health Data Science and Statistics. Recent projects include the analysis of patient reported outcomes in multiple sclerosis, estimation of reproduction number for COVID19, and the impact of COVID-19 on mental health. Past projects also include predictive analytics for social housing and telecommunication industry.
I was Stage 1 Tutor for BSc (Hons) Mathematics for three years (2018 – 2021).
