Simon Fraser University

In this talk I will present a series of works derived from the framework of physics inspired graph neural networks (GNN). The central premise is a GNN can be seen as the discretisation of a learnable dynamical system over a graph, this allows to...

Glass Klein bottles? Sure! How about knots and knot-compliments? A Boys Surface? Plenty of topological manifolds work well in glass. With good fortune, SFU's glass-blower, Lucas Clarke, will demonstrate his art in making mathematical manifolds in...

This talk presents the Proximal Galerkin (PG) method, a high-order numerical method for solving variational problems with inequality constraints. PG combines two foundational ideas from applied mathematics: Galerkin discretizations of partial...

In this talk, we study cut-generating functions in the setting of the Gomory-Johnson group relaxations for integer programming. We address an open question: whether every facet (extreme function) for a finite cyclic group relaxation injects into the...

Given a complex Lie group G of adjoint type, the wonderful compactification Y(G) (originally described by work of DeConcini-Procesi) is a compactification of G by a divisor with simple normal crossings. These groups are specified by their Dynkin...

The analysis of why a specific MIP instance is infeasible formally can be reduced to computing an Irreducible Infeasible Subset (IIS) of the constraints. Unlike the case of LP, for MIP there is no useful duality that can be employed to facilitate...

We analyze how strategic customers and providers respond to delay information in a matching system. Using Markovian queueing models and equilibrium analysis, we evaluate three disclosure policies (no information, binary, and occupancy) and identify...

I will present some recent progress in the study of Hilbert schemes Hilb ⁡ d ( A n ) of d points in affine space. Specifically, I will describe some recent examples of elementary components of Hilbert schemes of points. One infinite family of these...

Applying robust optimization often requires selecting an appropriate uncertainty set both in shape and size, a choice that directly affects the trade-off between average-case and worst-case performances. In practice, this calibration is usually done...

This work investigates the integration of machine scheduling and personnel allocation problems. In machine scheduling, the goal is to find the optimal assignment of jobs to machines within a given time horizon, considering processing times and...