Seminars

ABSTRACT In the presence of closely located inclusions in elastic composite materials consisting of inclusions and a matrix of different material properties, the stress represented by the gradient ...

ABSTRACT Markov chain Monte Carlo (MCMC) is a powerful and well-known class of methods aimed to sample from probability distributions....

ABSTRACT Deep neural networks have brought transformative changes in areas such as image recognition and healthcare, yet their underlying theoretical principles remain somewhat elusive....

ABSTRACT We study the application of well-known physics-informed neural networks (PINNs) for solving non-smooth PDE-constrained optimization problems....

ABSTRACT In this talk, we discuss some recent results for photonic and quantum interacting systems....

ABSTRACT In the era of big data, the analysis of large scale text and network data has become a widely studied hot topic....

ABSTRACT We will consider a class of $n$th-order linear ordinary differential equations with a large parameter $u$....

ABSTRACT In this talk, I will present a sharp local well-posedness result for spherically symmetric solutions to quasilinear wave equations with rough initial data, when the spatial dimension is th...

ABSTRACT The goal of this talk is to show you a gallery of my recent works focusing on inverse problems with various applications ranging from image processing, computer graphics, and dynamic ident...

ABSTRACT We will discuss some L^2 restriction estimates for smooth compact surfaces in R^3 with affine surface measure and certain powers thereof....