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My research is centred around the famous Erdos-Ko-Rado (EKR) Theorem. I was first introduced to this theorem through an application in computer science, and later learned about its roots in pure mathematics. This is a research area that has grown so...

Let X be your favorite type of algebraic structure. For example, X could be the class of quadratic forms, algebras or algebraic varieties. To estimate the complexity of X, you might consider the following natural question: how many algebraically...

Infectious disease outbreaks have precipitated a profusion of mathematical models. Epidemic curves predicted by these models are typically qualitatively similar, despite distinct model assumptions, but there is no theoretical explanation for this...

Abstract TBA

Model categories provide a powerful framework for abstract homotopy theory, but their complexity often makes them difficult to classify. By focusing on finite categories, especially grids, we gain a combinatorial setting where the problem becomes...

Differential equations can be studied from a purely geometric point of view, translating many constructions from finite-dimensional differential geometry into their language. This approach helps to clarify such notions as symmetries, conservation...

We are extremely pleased to announce that Dr. Inwon Kim, Professor of Mathematics at UCLA, will deliver an upcoming lecture in the Hugh C. Morris Lecture Series. Dr. Kim is internationally recognized for her influential work in analysis and PDEs...

An abstract discrete dynamical system consists of a set X and a self-map f from X to itself. Dynamics studies the orbits of points of X under repeated application of f. When X and f are defined by polynomials, algebraic geometry comes into play, and...

We obtain symmetry results of the solution to some overdetermined problems related to the eigenvalue equation on a weakly star shaped annular domain in space forms. If the associated P-function is constant on the boundary, then we get a Serrin type...

Throughout scientific and commercial domains, we are often interested in separating mixed signals into their component sources. Supervised deep learning is state-of-the-art when large and well-labeled datasets can be used. But in many applications...