What does the transportation of soil have to do with cloud formation and artificial intelligence? If you're Professor Alessio Figalli, then the concept relates to the optimal transport theory, a field of study for which he won the Fields Medal in 2018.
Optimal Transport is used to calculate the best way of moving resources from where they are found to where they need to be. Historically, it dates to 1781, when the French government was looking for the most economical way of moving soil from one area to another, and the field has developed in the years since then.
Prof Figalli studied at the prestigious Scuola Normale Superiore in Pisa, where he completed his doctorate in a single year, before moving to the University of Texas in Austin. What Prof Figalli realised was that if you could minimise the “transport cost” of particles in a cloud, you could calculate the optimal path, and make predictions of how clouds change their shape. He had pondered on this problem for seven years before he and his colleagues finally made a breakthrough in 2012.
Since then, Prof Figalli has endeavoured to apply optimal transport theory to as many areas as possible, in topics as diverse as soap bubbles to crystal formation. Now, his latest work is in using the theory to optimise machine learning, especially in Generative Adverserial Networks (GANs).
Prof Figalli has collaborated on more than 130 papers, a prodigious output for any mathematician, let alone one of his young age. However, he is up for the challenge, even if it means the occasional failure: "The way I try to think about (maths) problems is that even if I don't solve them, I'm still learning something. Perhaps there is failure... but from failure you learn."
Currently, Prof Figalli is FIM Director and Professor of Mathematics at ETH Zurich, Switzerland. He has won numerous awards in addition to the Fields Medal 2018, including the 2020 Falling Walls Award in Engineering and Technology, and in 2018, he was made a Knight of the Order of Merit of the Italian Republic.