Research Projects

Enhancing Care and Anomalies Detection in a Common Eye Disease with Deep Learning

This project is open to MSci student.

Investigation of novel protein structures in human disease

Investigating novel uncharacterised protein sequences in health and disease using AlphaFold and other folding tools

This project is open to MSci student.

Genetic Landscape of Rare Disease Patients

Analysing a database of 6000+ genetic patients with rare diseases collected since 2013 at London hospitals

This project is open to MSci student.

Alignment in Complex Genomic Regions

Developing artificial chromosomes reference panels for alignment in complex regions of the human genome

This project is open to MSci student.

BayesConformPred

Leveraging conformal prediction with estimated uncertainty for disease detection

This project is open to MSci student.

EyeNomaly

Anomaly detection in medical images using unsupervised learning

This project is open to MSci student.

Doctor in the Loop

Improve learning efficiency by closing the loop

This project is open to MSci student.

QualifEye

Unsupervised representation learning approach for image quality evaluation

This project is open to MSci student.

SynthEye

Creating synthetic retinal image augmentations with deep learning

This project is open to MSci, MRes and PhD students.

Eye-archical Tissue Segmentation

Using a hierarchical probabilistic framework to identify retinal tissue layers

This project is open to MSci, MRes and PhD students.

Eye2Gene

Decision support systems for genetic diagnosis of inherited retinal diseases.

This project is open to MSci, MRes and PhD students.

EyeCon

Decision support systems for keratoconus and other corneal ectasias.

Phenopolis Genomic Browser

A genetic browser than integrates with the Human Phenotype Ontology.

This project is open to MSci computer science and software engineering students.

KeraScreen

Detection of subclinical keratoconus from corneal imaging

This project is open to MSci student.

EyeNote

Extracting genetic information from clinical notes

This project is open to MSci student with interest in natural language processing.