Title: Computational Approaches to Optimization Problems in Inhomogeneous Rods and Plates Abstract: In this talk, we will show the experiments of the vibration of plates to generate Chladni's figures and […]
Title: Understanding scientific fields with network analysis and topic modeling Abstract: As scientific disciplines get larger, it becomes impossible for an individual researcher to be familiar with the entire body of […]
Title: Approximating Quasi-Stationary Distributions with Interacting Reinforced Markov Chains Abstract: An important question in ecology is what conditions must be met for a population of interacting species to coexist. In […]
Title: Kolmogorov, Onsager and a Dyadic Model for Turbulence Abstract: We will briefly review Kolmogorov’s ( 41) theory of homogeneous turbulence and Onsager’s ( 49 ) conjecture that in 3-dimensional […]
Title: Mathematical modeling of polymerization processes in physiology Abstract: Polymerization, or aggregation, is essential for many physiological systems. For example, the emergence of a fibrin polymer mesh during the formation of […]
Title: Randomized Sums of Graph Spectra Abstract: The adjacency matrix of an Erdős-Rényi-Gilbert graph is a random symmetric matrix whose entries are Bernoulli random variables. These entries, modulo the constraints […]
Title: Data-driven large eddy simulation of atmospheric turbulence Abstract: Over the last few years, machine learning has been critical in science and engineering and emerged as a data-driven turbulence model. […]
Title: Scattering Resonances Through Subwavelength Holes and Their Applications in Imaging and Sensing Abstract: The so-called extraordinary optical transmission (EOT) through metallic nanoholes has triggered extensive research in modern plasmonics […]
Title: Using Mutual Information of Hypergraph Compressions for Clustering Abstract: Hypergraphs are often used to represent higher order observed relationships between subjects of study. In particular, the vertices of a […]
Title:Geometric Scattering on Measure Spaces Abstract: Geometric Deep Learning is an emerging field of research that aims to extend the success of convolutional neural networks (CNNs) to data with non-Euclidean […]
Title: Identification of the order of semilinear subdiffusion with memory Abstract: See attached abstract
Title:Inferring birth and death rates from population size time series data Abstract: Models of population dynamics are usually formulated and analyzed with net growth rates. However, separately identifying birth and […]
