Martin Keleman is a PhD student on the Mathematical Genomics and Medicine programme, supervised by Carl Anderson at the Wellcome Trust Sanger Institute. His research focuses on developing practical machine learning methods for GWAS data, that will improve our understanding of how genetic differences influence variation in complex disease risk. He is now being jointly supervised by Chris, and we hope to pursue a rigorous comparison of ML and traditional statistical methods for various GWAS tasks.