Alexander Iannantuono

Hi!

I’m a software developer at Softree Technical Systems where I work on a variety of modelling-based projects related to road design.

I received my MSc. in mathematics from UBC - Okanagan, working with Dr. Yves Lucet and Dr. Warren Hare. My research focused on using regularization for continuous optimization in road design applications. I am grateful to have been partially funded by the FRQNT B1X scholarship.

I completed my joint BSc. at McGill in mathematics and computer science. During my studies, I mainly worked in the Oberman Lab with a handful of great researchers to whom I am indebted to.

Some non-academic activities that I enjoy are cycling, skiing and badminton.

small talk topics

My surname is pronounced as [ja.nan.’two.no]
I enjoy tinkering
Cooking, see /misc/culinary
Homelab-ing

news

Oct 23, 2020	I will be giving a talk on No-collision transportation maps at COCANA on ~~January 14~~ March 4, 2021 via Zoom.
Jul 05, 2020	Our work on using Out-of-Distribution (OOD) data for DNN calibration has been accepted to the UDL workshop!

selected publications

JSC

No-Collision Transportation Maps

L. Nurbekyan, A. Iannantuono, and A. M. Oberman

2020

Abs DOI HTML PDF

Transportation maps between probability measures are critical objects in numerous areas of mathematics and applications such as PDE, fluid mechanics, geometry, machine learning, computer science, and economics. Given a pair of source and target measures, one searches for a map that has suitable properties and transports the source measure to the target one. Here, we study maps that possess the no-collision property; that is, particles simultaneously traveling from sources to targets in a unit time with uniform velocities do not collide. These maps are particularly relevant for applications in swarm control problems. We characterize these no-collision maps in terms of half-space preserving property and establish a direct connection between these maps and binary-space-partitioning (BSP) tree structures. Based on this characterization, we provide explicit BSP algorithms, of cost \(O(n \log n)\), to construct no-collision maps. Moreover, interpreting these maps as approximations of optimal transportation maps, we find that they succeed in computing nearly optimal maps for \(q\)-Wasserstein metric (\(q = 1, 2\)). In some cases, our maps yield costs that are just a few percent off from being optimal.