Speaker Biography

Saurabh leads the AI research team at Babylon. He has been with Babylon since 2016. In this time he has guided the team to develop Babylon’s AI for the development of the triage, diagnostic and predictive models for healthcare, and applied the team’s research in Bayesian Machine Learning and Causal inference. Prior to Babylon, Saurabh spent time as a post-doctoral researcher at the MRC Centre for Outbreak Analysis & Modelling at Imperial College London. This work was funded by the Gates Foundation in collaboration with the CDC, and focused on the development of novel statistical machine learning methods to estimate poliovirus transmission from genetic sequence data. Before his post-doctoral work, Saurabh completed his PhD in population genetics from Imperial College London, investigating the population genetics of Tuberculosis and predicting new drug targets from whole genome sequence data.

Talk Abstract

In this talk, I will discuss our work at Babylon, building digital health products to provide affordable and accessible healthcare to everyone on earth. AI is central to our mission, driving the creation of products which empower users and clinicians with up-to-date information on their health, and that of their patients. The potential impact of AI in healthcare is immense, but there are also sizeable challenges and considerations that must be addressed. I will discuss some of the imperatives for AI in healthcare and some of the key design decisions that must be considered when moving solutions from R&D into the real world. Finally, I will discuss some of our latest research and its implications for delivering personalised medicine.