Bio

Risa is a PhD student at the British Antarctic Survey and the University of Cambridge and an Enrichment student at The Alan Turing Institute. Her work focuses on developing machine learning techniques to obtain better future projections of climate extremes in megacities and assessing their potential impact on urban infrastructure resilience.

She has a masters in computational statistics and machine learning from UCL and studied undergraduate physics at Imperial College London. She worked at IBM as a technology consultant for two years before discovering the world of machine learning research.

Research interests

With increasing climate variability and rising mean temperatures, extreme events are expected to become more frequent and severe in the next few decades. Currently robust climate projections for cities are lacking, which presents a major source of uncertainty in predicting future impacts. Her work aims to address this urgent problem. Her passion lies in contributing to the scientific understanding of climate change and finding out what developing cities can do to reduce its societal and economical impact.

Currently her favourite machine learning tool is Gaussian processes and her aim at the Turing is to become “more Bayesian”.