Yinghui Wei

Academic profile

Dr Yinghui Wei

Associate Head of School (Resources)
School of Engineering, Computing and Mathematics (Faculty of Science and Engineering)

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):

Goal 03: SDG 3 - Good Health and Well-beingGoal 04: SDG 4 - Quality EducationGoal 05: SDG 5 - Gender EqualityGoal 10: SDG 10 - Reduced InequalitiesGoal 11: SDG 11 - Sustainable Cities and CommunitiesGoal 12: SDG 12 - Responsible Consumption and ProductionGoal 14: SDG 14 - Life Below WaterGoal 16: SDG 16 - Peace, Justice and Strong InstitutionsGoal 17: SDG 17 - Partnerships for the Goals

About Yinghui

I am Associate Head of School (Resources) and Associate Professor of Statistics in School of Engineering, Computing and Mathematics at University of Plymouth. I lead the MSc Health Data Science and Statistics, chair School Equality Diversity and Inclusion Committee, and co-lead the Big Data group. I led the School's successful Athena Swan Bronze application in 2020, and led a cross-faculty team for the establishment of the new MSc Health Data Science and Statistics for September 2022 launch. I also hold an honorary/visiting appointment in Bristol Medical School at University of Bristol. I am an associated member of National Institute for Health and Care Research (NIHR) Applied Research Collaboration South West Peninsula (PenARC). Prior to joining Plymouth, I was Investigator Scientist (Statistician) in MRC Clinical Trials Unit at UCL, Career Development Fellow in Biostatistics in MRC Biostatistics Unit at University of Cambridge, and Research Fellow in School of Mathematical Sciences, University of Nottingham. I completed my PhD and MSc in Statistics in 2008 and 2004, respectively, from the School of Mathematics, The University of Manchester.  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 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.

Research interests
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 milliaon 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. My specific methodological research areas include:

  • Bayesian inference
  • Clinical prediction models
  • Statistical methods for evidence synthesis
  • Modelling and analysis of infectious diseases epidemiology
  • Survival analysis

I have worked in various disease areas, including 

  • COVID-19
  • Zika virus
  • Cardiovascular diseases
  • Autoimmune disorders
  • Renal diseases
  • Cancer
  • Mental illnesses
  • Neurodegenerative diseases
  • Tuberculosis
  • Hospital-acquired infectious diseases, such as Vancomycin-Resistant Enterococci

In 2021, I was awarded an MRC fellowship to work within the COVID-19 Longitudinal Health and Wellbeing National Core Study to investigate the long-term effects of COVID-19 on population health. In 2009-2012, I was an MRC Career Development Fellow in Biostatistics at Cambridge, where I delivered methodological research in multivariate meta-analysis of multiple outcomes and multiple treatments. In 2012-2013, I worked as a methodological Statistician at the MRC London Hub for Trials Methodological Research, where I conducted methodological research in meta-analysis of time-to-event outcomes. I co-developed a statistical package, ipdfc in Stata, to reconstruct individual participant time-to-event data from published Kaplan-Meier curves, which has been used by researchers worldwide (link).

Externally funded projects

Selected Seminars/Talks/Posters

  • 2024: Invited talk: "A comparison of methods for externally validating the kidney donor risk index in the UK kidney transplant population", 7th International Conference on Econometrics and Statistics (EcoSta 2024), Beijing.
  • 2023: Invited talk: "Why and how to get research funding", Royal Statistical Society International Conference, Young Statistician Session, Harrogate.
  • 2023: Invited talk: "Patient characteristics associated with clinically coded long COVID: an OpenSAFELY study using electronic health records", Institute of Epidemiology, University of Münster, Germany
  • 2023: Invited talk: "How I got my first grant", Early Career Researcher Funding Workshop, School of Engineering, Computing and Mathematics, University of Plymouth
  • 2023: Webinar: "Improved health research and practice through advancing statistical methods and applications - sharing experience from constructing a REF2021 impact case study", Association of British Chinese Professors, Impact Case Webinar Series.
  • 2023: Seminar: "Factors associated with clinically coded long COVID: big data analytics using OpenSAFELY", Community and Primary Care Research Group, University of Plymouth
  • 2022: Seminar: "What is a Trusted Research Environment?", Centre for Mathematical Sciences, University of Plymouth
  • 2022: Poster: "Risk factors for long COVID: big data analytics using OpenSAFELY", Royal Statistical Society International Conference, Aberdeen
  • 2022: Contributed talk: "Bivariate copula regression models for semi-competing risks", Royal Statistical Society International Conference, Aberdeen
  • 2022: Invited talk: "Using data to improve public health: COVID secondment - Overview of Experience", COVID-19 Longitudinal Health and Wellbeing National Core Study Workshop, UCL
  • 2022: Invited talk: "Risk factors for long COVID", COVID-19 Longitudinal Health and Wellbeing National Core Study Workshop, UCL
  • 2020: Invited talk, "The arts and techniques of online teaching for mathematics and statistics", Shanghai Polytechnic University
  • 2019: Contributed talk, "Estimating the correlation between bivariate survival endpoints", Royal Statistical Society International Conference, Belfast
  • 2019: Invited talk, "Statistical Applications in Medical Sciences", INSPIRE Interdisciplinary Meeting, Plymouth.
  • 2018: Invited talk, "Survival analysis of patients following kidney transplantation" (with Lexy Sorrell), South West Transplant Centre Annual Transplant Day, Totnes.
  • 2018: Invited talk, "Survival analysis: from individual level data to aggregate data", Yunnan University, China.
  • 2018: Invited talk, "Survival analysis: from individual level data to aggregate data", AUFE, China.
  • 2017: Invited talk, "Restricted mean survival time: from individual level data to aggregate data", CMStatistics 2017, University of London, London.
  • 2017: Session chair, "Recent Advances in Research Synthesis Methods", CMStatistics 2017, University of London, London.
  • 2017: Contributed talk, "Using published Kaplan-Meier curves to reconstruct time-to-event data for secondary analyses", Royal Statistical Society International Conference, Glasgow. 
  • 2017: Contributed poster, "Hierarchical Bayesian models for road traffic accidents", Royal Statistical Society International Conference, Glasgow. 
  • 2016: Invited lecture, "Introduction to Design and Analysis of Clinical Trials", postgraduate summer school, University of Electronic Science and Technology of China, Chengdu.
  • 2015: Invited seminar, "The use of restricted mean survival time in meta-analysis of clinical trials with time-to-event outcomes". University of Exeter, Exeter.
  • 2014: Invited seminar, "Meta-analysis of survival data using restricted mean survival time", University of Essex, Colchester.
  • 2013: Contributed talk, "Analysis of survival data from trials with non-proportional hazards". Clinical Trials Methodology Conference: Methodology Matters, Edinburgh. 
  • 2013: Contributed talk, "Network Meta-analysis", Methodology Theme Meeting, MRC Clinical Trials Unit, London.
  • 2012: Contributed poster, "Bayesian multivariate meta-analysis with many outcomes", 33rd Annual Conference of International Society for Clinical Biostatistics, Bergen.
  • 2011: Contributed talk, "Bayesian multivariate meta-analysis with many outcomes", Methods in Meta-analysis Meeting, Royal Statistical Society, London.
  • 2010: Internal Seminar, "Multivariate meta-analysis with multiple outcomes", MRC Biostatistics Unit, Cambridge. 
  • 2010: Invited lecture, "Introduction to Meta-analysis", Shanghai Nottingham Systematic Review Course, Shanghai Jiao Tong University, Shanghai. 
  • 2007: Poster presentation, "An epidemic model for discrete data in dynamic population", Manchester Research Student Conference in Statistics and Probability, University of Manchester.
  • 2007: Contributed talk, "Statistical inference about epidemics in dynamic population", Research Student Conference in Statistics and Probability, Durham, UK.

Conferences organised

  • Nov 2022: EPSRC IAA Workshop: Industry-Academia Collaboration for Health Data Science
  • Sept 2022: Health Data Science for COVID-19 Research, Invited Session, Royal Statistical Society International Conference
  • Mar 2021: LMS Women in Mathematics Day
  • Oct 2020: Joint RSS South West Local Group - Impact Lab event: Early Career Researchers' Health Data Science Symposium.
  • 2018 – 2022: RSS South West Local Group Meeting Programmes

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).