Dr Raziyeh Mohammadi
- Position: Research Fellow
- Areas of expertise: Machine learning in healthcare; Risk prediction models; longitudinal data analysis; multilevel models; survival analysis; Bayesian inference
- Email: R.MohammadiFartkhouni@leeds.ac.uk
- Location: Worsley Building
- Website: LinkedIn | Googlescholar
Profile
I am currently a Research Fellow in the Data Science team at the Academic Unit for Ageing and Stroke Research (ASR), University of Leeds.
I obtained my PhD in Statistics from Isfahan University of Technology, Iran, in 2021. During my PhD, I focused on developing robust statistical methods for analysing longitudinal and correlated data, addressing challenges such as heavy tails and skewness. I introduced a robust linear mixed-effects model for heavy-tailed and skewed longitudinal data and applied Bayesian inference for parameter estimation.
I subsequently worked for two years as a Research Fellow at Duke-NUS Medical School, National University of Singapore. In this role, my work centred on leveraging advanced statistical and machine learning methods to analyse clinical datasets. I developed and implemented risk prediction models to identify cognitive decline in eary Parkinson’s disease using multimodal clinical and blood biomarkers.
Research interests
My key research interests include:
- Machine learning in clinical data, particularly for risk prediction and early detection of disease
- Longitudinal data analysis
- Multilevel models
- Survival analysis
Qualifications
- PhD in Statistics
Research groups and institutes
- Academic Unit for Ageing and Stroke Research