How could AI techniques be used to best improve the living standards of people around the world? This is the main question of interest for Laurens Arp, a Master student who joined the ADA research group in November 2019. He is currently working on his Master Thesis under the supervision of Mitra Baratchi and Holger Hoos. The project is about the data-driven evaluation and optimization methods of geographical regions.
The main focus of the project will be on (spatial) representation learning. Current methods would not sufficiently address the problem yet, as most approaches will either focus too much on spatial structure instead of how this structure affects the features of a neighborhood, or are aimed too much at encoding similarity rather than interaction. Once a suitable representation has been found, machine learning and deep learning could be used to automatically learn the relationship between geographical features and the measures one might like to use to evaluate a region. If the resulting model is sufficiently accurate, it could then be used to rate the quality of region configurations generated by an optimization algorithm, allowing for the optimization of the development of the region.