Biography
Thalia Seale has a background in Mathematics and Statistics, holding a BSc in Mathematical Sciences from the University of Durham (2021) and an MSc in Statistical Science from the University of Oxford (2022). She is passionate about applying machine learning to enhance clinical insights and has contributed to a range of research projects across social, environmental, and public health domains.
Currently, she is a doctoral student in the Health Data Science CDT, working with Dr. Abhirup Banerjee at the MultiMeDIA lab, and co-supervised by Prof. Vicente Grau and Prof. Blanca Rodriguez in the Department of Computer Science. She has also previously collaborated with Prof. Konstantinos Kamnitsas as part of the CDT program.
Research Interests
- Cardiac motion
- Ventricular anatomy
- Generative models
- Multimodality
Current Projects
Automated personalised 4D heart modelling for disease prediction
Research Groups
Related Academics
Key Papers
Modelling Multi-Phase Cardiac Anatomy Using Point Cloud Variational Autoencoders (2024, ISBI).
Feasibility and benefits of joint learning from MRI databases with different brain diseases and modalities for segmentation (2024, MIDL).
Modelling Multi-phase Cardiac Anatomy with Generative Deep Learning (2024, CinC) (Winner of Bill and Gary Sanders Poster Award).
Awards and Prizes
Winner of Bill and Gary Sanders Poster Award, CinC, 2024
