Past Events

A fundamental challenge in infection biology is predicting the dynamics of within-host microbial growth and immune activation. However, data typically comes as static snapshots, limiting our ability to test theories. Therefore, we established live...

The Polya group Po(K) of a Galois number field K coincides with the subgroup of the ideal class group Cl(K) of K consisting of all strongly ambiguous ideal classes. We prove that there are only finitely many imaginary abelian number fields K whose...

Bregman proximal-type algorithms, such as mirror descent, are popular in optimization and data science for effectively exploiting problem structures and optimizing them under tailored geometries. However, most of existing convergence results rely on...

Measures provide valuable insights into long-term and global behaviors across a broad range of dynamical systems. In this talk, we present our recent research efforts that employ measure theory and optimal transport to tackle core challenges in...

In this talk, we consider a notion of stability for solutions of random optimization problems based on small perturbations of the input data and inspired by the technique for proving CLT using Stein's method as illustrated with examples by Chatterjee...

I will start by giving a broad overview of our seminar so far, outlining the way in which characteristic classes arise from the cohomology of classifying spaces. When the coefficients for cohomology are the real numbers, the characteristic classes...

Infectious diseases are complex systems across many scales. In this talk, I will use mathematical models to investigate a range of cross-scale questions in infectious disease eco-evolutionary dynamics. I will begin by modelling the transition from...

We provide a detailed study on effective versions of the celebrated Bilu's equidistribution theorem for Galois orbits of sequences of points of small height in the N-dimensional algebraic torus, identifying the qualitative dependence of the...

Highly evolved animals continuously update their knowledge of social factors, refining movement decisions based on both historical and real-time observations. Despite its significance, research on the underlying mechanisms remains limited. In this...

Particle Swarm Optimization (PSO) algorithm is based on swarm intelligence and widely used in the field of Artificial Intelligence. Like many other nature-inspired metaheuristic algorithms, it is already widely used to tackle all sorts of hard...