Sigrid Passano Hellan
I’m interested in probabilistic machine learning and its application to environmental problems. My PhD project is about finding methods for efficiently sampling urban air pollution. New low-cost sensors mean many more locations can be sampled, but with higher uncertainty. We’re using Bayesian optimisation to model pollution levels and uncertainties in an area, and to determine where to sample next. Our goal is for the method to be usable for real-time sampling, e.g. directing a person with a sensor around a town of interest.
I’m a member of the EPSRC Centre for Doctoral Training in Data Science, supervised by Nigel Goddard and Chris Lucas.
Links: email | personal website | google scholar | github
PhD Data Science 2022 (ongoing)
CDT in Data Science, University of Edinburgh
MScR Data Science, 2019
University of Edinburgh
MEng Electrical and Electronic Engineering, 2018
Imperial College London