Statistics postdoc tames decades-old geometry problem
To the surprise of experts in the field, a postdoctoral statistician has solved one of the most important problems in high-dimensional convex geometry.
The new paper by Yuansi Chen gets at the Bourgain slicing problem via a far-reaching question about convex geometry called the KLS conjecture. This 25-year-old conjecture, which asks about the best way to slice a shape into two equal portions, implies Bourgain's conjecture. What’s more, the KLS conjecture lies at the heart of many questions in statistics and computer science, such as how long it will take for heat to diffuse through a convex shape, or how many steps a random walker must take from a starting point before reaching a truly random location.
Read the full article in external pageQuanta Magazine.
Yuansi Chen is a postdoctoral researcher at the Seminar for Statistics (SfS) and the ETH Foundations of Data Science (ETH-FDS) at ETH Zürich under the supervision of Professor Peter Bühlmann. Yuansi will be joining the Department of Statistical Science at Duke University as an Assistant Professor in Spring 2021.
