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# Applied and Computational Mathematics

**DMS Applied Mathematics Seminar**

Mar 23, 2018 02:00 PM

Parker Hall 328

Speaker:

**Professor Jianliang Qian**, Michigan State University.

Title: Babich-like ansatz for point-source Maxwell's equations

Abstract: We propose a novel Babich-like ansatz consisting of an infinite series of dyadic coefficients (three-by-three matrices) and spherical Hankel functions for solving point-source Maxwell's equations in an inhomogeneous medium so as to produce the so-called dyadic Green's function. Using properties of spherical Hankel functions, we derive governing equations for the unknown asymptotics of the ansatz including the traveltime function and dyadic coefficients. By proposing matching conditions at the point source, we rigorously derive asymptotic behaviors of these geometrical-optics ingredients near the source so that their initial data at the source point are well defined. To verify the feasibility of the proposed ansatz, we truncate the ansatz to keep only the first two terms, and we further develop partial-differential-equation based Eulerian approaches to compute the resulting asymptotic solutions. Numerical examples demonstrate that our new ansatz yields a uniform asymptotic solution in the region of space containing a point source but no other caustics.

Graduate students are especially urged to attend.

**DMS Applied Mathematics Seminar**

Feb 23, 2018 02:00 PM

Parker Hall 328

Speaker:

**Martin Short**from Georgia Tech

http://people.math.gatech.edu/~mshort9/index.shtml

Title: Modeling and predicting urban crime – How data assimilation helps bridge the gap between stochastic and continuous models

Abstract: Data assimilation is a powerful tool for combining mathematical models with real-world data to make better predictions and estimate the state and/or parameters of dynamical systems. In this talk I will give an overview of some work on models for predicting urban crime patterns, ranging from stochastic models to differential equations. I will then present some work on data assimilation techniques that have been developed and applied for this problem, so that these models can be joined with real data for purposes of model fitting and crime forecasting.

**DMS Applied Mathematics Seminar**

Feb 02, 2018 02:00 PM

Parker Hall 328

Speaker:

**Lianzhang Bao**, Jilin University

Title: Traveling wave solutions in backward forward parabolic equation and others

Abstract: In the talk I will first derive backward forward parabolic equations from population dynamics via a biased random walk, then some properties and the existence of the traveling wave solutions to these equations will be discussed. Finally, some results related to partial differential equation control and inverse problems will be presented.

**DMS Applied Mathematics Seminar**

Dec 01, 2017 02:00 PM

Parker Hall 328

Speaker: **Prof. Peter Monk**, University of Delaware

Title: Inverse Scattering in a Waveguide

Abstract: I shall present a study of the inverse problem of determining the shape of inclusions in a sound hard waveguide using either frequency or time domain data. Mostly I will focus on the time domain problem and start by proving existence and uniqueness for the forward problem. Then I will derive a numerical method using time domain integral equations. For the inverse problem I will use the Linear Sampling Method due to Colton and Kirsch. After analysis of the time domain inversion scheme, I will provide a few numerical examples.

**DMS Applied Mathematics Seminar**

Nov 17, 2017 12:30 PM

Parker Hall 246

PLEASE NOTE **NEW TIME** AND **NEW PLACE**

Speaker: **Dr. Bo Liu,** Computer Science Department, AU

Title: Gradient, Semi-gradient and Pseudo-gradient Reinforcement Learning

Abstract: In this talk, I will present the establishment of a unified general framework for stochastic-gradient-based temporal-difference learning algorithms that use proximal gradient methods. The primal-dual saddle-point formulation is introduced, and state-of-the-art stochastic gradient solvers, such as mirror descent and extragradient are used to design several novel reinforcement learning algorithms. The finite-sample analysis is given along with detailed empirical experiments to demonstrate the effectiveness of the proposed algorithms. Several important extensions, such as control learning, variance reduction, acceleration, and regularization will also be discussed in detail.

**DMS Applied Mathematics Seminar**

Nov 10, 2017 02:00 PM

Parker Hall 328

Speaker: **Hyesuk Lee** (Clemson University)

Title: Finite element approximation and analysis for non-Newtonian fluid-structure interaction

Abstract: Numerical study of non-Newtonian fluid-structure interaction (FSI) provides significant challenges not only due to the strong coupling between the solid and fluid substructures, but also the complexity of fluid model in a moving domain. As a result, advances in numerical study for non-Newtonian FSI have been limited and there are still many open problems in the area.

In this talk both monolithic and decoupling approaches are considered for analytical and numerical studies of fluid-structure interaction problems, where the fluid is governed by a quasi-Newtonian or a viscoelastic fluid model. We will present finite element error estimates for a quasi-Newtonian FSI system and numerical results that show comparisons with a Newtonian FSI system. For a viscoelastic FSI problem we will discuss some issues with the stress boundary condition on the interface and present simulation results with/without interface stress boundary conditions.

**DMS Applied Mathematics Seminar**

Oct 20, 2017 02:00 PM

Parker Hall 328

We are fortunate to have

**Professor Ming-Jun Lai**<http://alpha.math.uga.edu/%7Emjlai/> from the University of Georgia to speak on the topic of matrix completion <https://en.wikipedia.org/wiki/Matrix_completion>.

Title: On Recent Development of Matrix Completion.

Abstract: I shall first introduce the research on matrix completion based on Netflix problem. Then I will survey some classic methods based on various approaches. In particular, I will explain some recent approaches based on alternating minimization methods including least squares, steepest descent, and Riemann gradient descent techniques. Finally, I shall explain our method of Alternating Projection Algorithm and present a convergence analysis under some conditions. Linear convergence will be shown under a sufficient condition. I will end my talk with numerical experimental results to demonstrate our method is excellent in completing a matrix of low rank.

**DMS Applied Mathematics Seminar**

Oct 06, 2017 02:00 PM

Parker Hall 328

Speaker: **Prof. Xu Zhang,** Mississippi State University

Title: Immersed Finite Element Methods for Interface Problems (Basic idea, Development, Analysis, and Applications)

Abstract: Simulating a multi-scale/multi-physics phenomenon often involves a domain consisting of different materials. This often leads to the so-called interface problems of partial differential equations. Classical finite elements methods can solve interface problems satisfactorily if the mesh is aligned with interfaces; otherwise the convergence could be impaired. Immersed finite element (IFE) methods, on the other hand, allow the interface to be embedded in elements, so that Cartesian meshes can be used for problems with non-trivial interface geometry.

In this talk, we start with an introduction about the basic ideas of IFE methods for the second-order elliptic equation. We will present challenges of conventional IFE methods, and introduce some recent advances in designing more accurate and robust IFE schemes. Both a priori and a posteriori error estimation will be presented. Finally, we will demonstrate how IFE methods can be applied to more complicated interface model problems.

**DMS Applied Mathematics Seminar**

Sep 22, 2017 02:00 PM

Parker Hall 328

Speaker: **Hans-Werner van Wyk**

Title: Clenshaw-Curtis Type Rules for Statistical Integrals

Abstract: In statistics, many commonly encountered quantities take the form of density weighted integrals. This talk treats their numerical estimation within the Chebyshev approximation framework. In particular, we discuss how a generic one dimensional density function can be incorporated into the construction of Clenshaw-Curtis type quadrature rules, either through an adjustment of the quadrature weights or by generating a set of quadrature nodes that satisfies the optimal spacing property in terms of the density-weighted uniform error. We consider a variety of density functions, including those that are piecewise continuous, or have unbounded support. The accompanying numerical experiments illustrate the behavior and performance of the resulting quadrature rules and offer a comparison with a variety of existing approaches for estimating density weighted integrals.

**Applied Mathematics Seminar/Colloquium Yuesheng Xu**

Feb 10, 2017 02:00 PM

Parker Hall 250

Please note time: 2:00 pm

Speaker: Professor Yuesheng Xu (Sun Yat Sen University, China)

Title: Mathematics in Data Science

Abstract: We shall discuss several mathematical problems crucial in data science. They include representation of data, mathematical models of recovering a fact from raw data, matching learning and solving optimization problems in data analysis.

Faculty host: Yanzhao Cao

**Applied Mathematics Seminar**

Jan 27, 2017 02:00 PM

Parker Hall 328

Speaker: ** Dr. Yi Wang,** Professor and Chair at Auburn University at Montgomery (AUM).

Title: Sparse representation with non-linear Fourier atoms

Abstract: In this talk, we study the sparse representation of a finite energy signal with intrinsic mode functions in a dictionary consisting of non-linear Fourier atoms. Each non-linear Fourier atom is a mono-component with a physically meaningful non-negative instantaneous frequency. The sparse representation is obtained adaptively by an orthogonal matching pursuit using a two-level greedy search. It is demonstrated that the representation has efficient energy decay in error compared to the Fourier expansion and wavelet expansion.

Keywords: sparse representation, non-liner Fourier atom, orthogonal matching pursuit, trust-region-reflective search.

Last Updated: 09/25/2015