# School of Mathematics

## Inverse problems for quantum graphs

## Compositional inductive biases in human function learning

## Online Learning in Reactive Environments

## Permutation property testing

## How will we do mathematics in 2030 ?

We make the case that over the coming decade, computer assisted reasoning will become far more widely used in the mathematical sciences. This includes interactive and automatic theorem verification, symbolic algebra, and emerging technologies such as formal knowledge repositories, semantic search and intelligent textbooks.

## Thresholds Versus Fractional Expectation-Thresholds

Given an increasing family F in {0,1}^n, its measure according to mu_p increases and often exhibits a threshold behavior, growing quickly as p increases from near 0 to near 1 around a specific value p_c. Thresholds of families have been of great historical interest and a central focus of the study of random discrete structures (e.g. random graphs and hypergraphs), with estimation of thresholds for specific properties the subject of some of the most challenging work in the area.

## A rigorous derivation of the kinetic wave equation

In this talk I will outline recent work in collaboration with Pierre Germain, Zaher Hani and Jalal Shatah regarding a rigorous derivation of the kinetic wave equation. The proof presented will rely of methods from PDE, statistical physics and number theory.

## Graph Sparsification via Short Cycle Decomposition

## The h-principle in symplectic geometry

Symplectic geometry, and its close relative contact geometry, are geometries closely tied to complex geometry, smooth topology, and mathematical physics. The h-principle is a general method used for construction of smooth geometric objects satisfying various underdetermined properties. In the symplectic context, h-principles typically give constructions of surprising exotica, and methods for detecting the basic flexible objects. We survey a number of results from the previous decade.