Most math scholars do their most impactful work when they are young, but Michele Pavon is experiencing the most productive research phase of his scientific life at age 72.
The Italian mathematician has broken the mold that many scholars in his field fall into –in more ways than one.
After almost half a century in academia, Michele Pavon has reinvented his scholarship with a focus on optimal transport theory, a relatively new field of mathematics that drives today’s machine learning.
Having shifted his focus to applied mathematics several times –publishing papers in top journals on research in statistics, physics, electrical engineering, and now the nascent field of optimal transport – Pavon has defied the field once again.
“Some scholars focus and don’t move out of their field, which is fine and very common in math. But I found in my career that challenging myself and delving into something new was profoundly productive,” he said from his new office. “It just so happened that I was always surrounding myself with curiosity and dedicating my time to fields that showed promise.”
Pavon’s academic journey is just as wide-spanning as his scholarly pursuits. Pavon joined NYU Abu Dhabi in the fall of 2022 through a long, illustrious journey that began in his hometown of Venice, where he walked the same halls as Galileo Galilei during his undergraduate degree at the University of Padova.
His curiosity and penchant for research led him to pursue a graduate program abroad, the only option for ambitious Italian scholars at the time. He landed at the University of Kentucky, where despite the culture shock for the young Venetian, he was immersed in a budding field of study that, in 1975, was the foundational precursor to how we live our life today.
After graduating, he continued with stints in American universities and others in Europe before returning to his alma mater of University of Padova. However, during this time, Pavon was always on the hunt for the next field of mathematics.
And in 2004, a breakthrough that would change his scientific life was made. Work of Erwin Schrödinger, the same of the quantum mechanical wave equation, was connected to a regularized form of optimal transport that Pavon would eventually launch a golden age in his scientific career.
Optimal transport is a field of math that he says is used in technology, machine learning, and even artistic creations.
It’s everywhere. Think about a movie; imagine a scene where the CGI needs a character to transform from a human to a bear. Those frames, how smooth that morphing happens, is governed by optimal transport theory.
Now working at NYUAD, he balances teaching and building on his impressive body of research for which he won the IEEE Control Systems Society 2017 George S. Axelby Outstanding Paper Award in 2017.
“NYUAD is a really incredible place to be; the facilities and the faculty are impressive. I’m looking forward to continuing this phase of my scientific career here,” he said.
