Student

Congratulations to PhD student Dominic Danks whose paper Derivative-Based Neural Modelling of Cumulative Distribution Functions for Survival Analysis has been accepted for presentation at AISTATS 2022.

Congratulations to PhD student Dominic Danks whose paper BasisDeVAE: Interpretable Simultaneous Dimensionality Reduction and Feature-Level Clustering with Derivative-Based Variational Autoencoders. has been accepted for presentation at the International Conference for Machine Learning 2021.

Congratulations to PhD student Woojung Kim whose will presenting his work on “Learning multimorbidity and its temporal dynamics with the Wright-Fisher Indian Buffet Processs” at the EcoStat 2021 and the International Society for Bayesian Analysis World Meeting 2021 conferences.

• Breaking Free with Artificial Intelligence: using data-driven insights to improve digital health support for substance use disorders

• Explainable AI for Multimodal Data Integration in Biomedical Applications

This project will seek to develop explainable probabilistic machine learning methods for multimodal data integration for biomedical applications. We will consider a number of theoretical and practical issues with data integration and explainable AI and develop robust statistically sound solutions to these research problems.

Congratulations to Zhiyuan Hu whose paper on the “The Repertoire of Serous Ovarian Cancer Non-genetic Heterogeneity Revealed by Single-Cell Sequencing of Normal Fallopian Tube Epithelial Cells” has been published in Cancer Cell. Read press coverage by the Daily Mail and the press release by the main funders Ovarian Cancer Action.

Congratulations to Kaspar Martens who has had two papers accepted into AISTATS 2020. Papers to be published soon.