Future Indonesian Tsunamis: Towards End-to-end Risk quantification (FITTER) Using high performance computing, uncertainty quantification, and economics to evaluate the risk posed to livelihoods by future tsunamis in Indonesia
Interpretable disease prediction models using supervised learning Evaluating supervised machine learning models for creating interpretable disease risk prediction models using electronic health records
Data-driven evaluation of treatments for type 2 diabetes Using machine learning to investigate differential effects of therapies on Type 2 diabetes patients
Investigating primary brain tumours Investigating the stratification of patients with primary brain tumours based on their predicted response to therapy
Automating translation by determining text difficulty Building a model to determine the features of text which make it more difficult for machine translation
Identifying potential disease causing variants in genetic data Developing an algorithm to identify disease causing variants in protein-coding regions of genes
Understanding differences in population estimates for Leeds Identifying how and why population estimates in Leeds differ between GP registers and the ONS
Ethics of machine learning in children's social care Researching whether the use of machine learning in children's social care can be ethically justifiable and what that would require in practice
Computational models of meaning change in Ancient Greek Developing computational models to automatically identify meaning change in the Ancient Greek language