Giulia Luise has recently obtained her PhD in Machine Learning at UCL, London. Her main research interest focuses on the interplay of optimal transport and machine learning. Her work so far has targeted using Optimal Transport distances as a loss function to learn and average distributions and as a geometric structure for optimization over the space of probability measures. Pior to that she obtained a Msc degree in pure maths at University of Pavia (Italy).
She is now a postdoctoral researcher at Imperial College, where she is working on reinforcement learning targeting applications in healthcare.
- Geometric Methods in Optimization and Sampling, Fall 2021. Visiting Graduate Student.