Dr Deepti Gurdasani

Profile

I am a clinical epidemiologist and statistical geneticist by background. After completing my MBBS and MD in Internal Medicine at Christian Medical College, Vellore, India, I completed my MPhil in Epidemiology and Biostatistics at the University of Cambridge in 2010, followed by a PhD in examination of genetic factors associated with disease in genetically diverse populations (2013). My subsequent work as a post-doctoral fellows at the Wellcome Sanger Institute focused on the study of population history, and historical migration across Africa (as co-lead of the African Genome Variation Project). As a senior staff-scientist at the Wellcome Sanger Institute, I co-led the Uganda Genome Resource Project (Gurdasani et al., Cell, 2019), studying genetic determinants of disease across ethnically diverse populations.

My research interests range from the development of new statistical methodology for population genetics, genome-wide association studies and genomic prediction, to developing new pipelines for drug discovery using large-scale multi-dimensional data.

Research

Groups members

I’m looking for talented and motivated PhD students and postdoctoral candidates interested in machine learning/deep learning methods and applications to large-scale clinical and genomic data to join my team. Please email me if you are interested.

Summary

My current work focuses on the development of novel methods in machine learning and their application to genomic and clinical prediction as well as inference of novel genomic drug targets. I work closely with Genomics England and co-lead the GeCIP project on prediction loss of function effects on health and disease within Genomics England.

Publications

Collaborators

Internal

• Prof. Sir Mark Caulfield
• Prof. Panos Deloukas
• Prof. Michael Barnes

External

• Prof. Mihaela Van der Schaar (University of Cambridge)
• Prof. John Overington (Medicines Discovery Catapult)

News

• African genomes sequenced (BBC News World Service (Science in Action), November 2019
• African genomes sequenced (BBC Radio 4 (Inside Science), October 2019