I am a postdoctoral researcher at Microsoft Research New England. My research focuses on the representation of geospatial phenomena in machine learning methods. I am also interested in the deployment of these methods in urban environments and to tackle climate change within both private and public sector organizations. In currently serve as a member of the board for Climate Change AI, a global nonprofit organization catalyzing impactful work at the intersection of machine learning and climate change. I completed my PhD at the University of Warwick and New York University. I was also an Enrichment student at the Alan Turing Institute and a Beyond Fellow at TUM / DLR.
A large share of all globally available data can in some shape or form be geo-referenced; mapped onto the sphere of planet Earth. This can be leveraged to train large "foundation" models that fuse different layers of spatial information and learn meaningful representations of every location on the planet. Such models will be transformative for private and public sector alike. From visionary moonsh...