Richard Moulange is a first-year PhD student, supervised by Dr Sach Mukherjee and Dr Oscar Rueda.

Current work:

Richard develops robust machine learning methods for analysing -omic data. His particular interests include (deep) transfer learning — especially domain adaptation — and causal inference. He is currently working with cancer genomic datasets to investigate how causal regularisation can improve model generalisability.

Useful links:

Richard's personal website is https://www.richardmoulange.com/.