Wei Zhu
Applied Math Seminar – Shan Zhao, University of Alabama
302 Gordon Palmer HallTitle: An overview of numerical algorithms for the Poisson-Boltzmann equation in biomolecular electrostatics Abstract: The Poisson-Boltzmann Equation (PBE) is a widely used implicit solvent model for the electrostatic analysis of solvated biomolecules. The numerical solution of the PBE is known to be challenging, due to the consideration of discontinuous coefficients, complex geometry of protein structures,
Applied Math Seminar – Husheng Li, University of Tennessee, Knoxville
302 Gordon Palmer HallTitle: Data Driven Quickest Change Detection: In the Spirit of Kullback, Kolmogorov and Shannon Abstract: Quickest change detection is to detect the unknown change of distribution of random process, which has a wide spectrum of applications in practice such as signal processing, financial data analysis and power grid operation, et al. In traditional quickest change
Applied Math Seminar – Wei Zhu, University of Alabama
302 Gordon Palmer HallTitle: A lower-order image denoising model for staircase reduction Abstract: In this talk, we will discuss a total-variation based lower-order image denoising model that is able to reduce the well-known staircasing phenomenon possessed by the Rudin-Osher-Fatemi model. To minimize the proposed variational model, we employ augmented Lagrangian method (ALM). Convergence analysis is established for the
Applied Math Seminar – Qin Wang, University of Alabama
302 Gordon Palmer HallTitle: Sufficient dimension reduction for high dimensional data Abstract: The high dimensional data generated from modern scientific discoveries introduces unique challenges to statistical modeling. Sufficient dimension reduction (SDR) is a useful tool to bridge the gap through projection subspace recovery. In this study, a new formulation is proposed based on the Hellinger integral of order
Applied Math Seminar – Xiaojing Ye, Georgia State University
302 Gordon Palmer HallTitle: Decentralized consensus optimization on networks with delayed and stochastic gradients Abstract: Decentralized consensus optimization has extensive applications in many emerging big data, machine learning, and sensor network problems. In decentralized computing, nodes in a network privately hold parts of the objective function and need to collaboratively solve for the consensual optimal solution of the
Applied Math Seminar – Evie A. Malaia, Communicative Disorders, University of Alabama
302 Gordon Palmer HallTitle: Mathematical models in cognitive neuroscience: advances and opportunities Abstract: High prevalence of neurodegenerative (Parkinson’s, Alzheimer’s) and neurodevelopmental (Autism spectrum disorders, ADHD) disorders in modern population increased the demand for precision therapeutic interventions. However, the current understanding of how those diseases develop and affect brain processing over time is incomplete, and testing of in-vivo interventions
Applied Math Seminar – Di Liu, Michigan State University
302 Gordon Palmer HallTitle: Multiscale Modeling and Computation of Optically Manipulated Nano Devices Abstract: We present a multiscale modeling and computational scheme for optical-mechanical responses of nanostructures. The multi-physical nature of the problem is a result of the interaction between the electromagnetic (EM) field, the molecular motion, and the electronic excitation. To balance accuracy and complexity, we adopt the semi-classical
Applied Math Seminar – Shibin Dai, University of Alabama
346 Gordon Palmer Hall 505 Hackberry Lane, Tuscaloosa, AL, United StatesTitle: Mean field models for thin film droplet coarsening Abstract: A thin liquid film coating a solid substrate is unstable and the late stage morphology is essentially quasiequilibrium droplets connected by an ultra thin film. Droplets exchange mass and coarsening occurs — the total number of droplets N(t) decreases while the average size of droplets
Applied Math Seminar – Brendan Ames, University of Alabama
346 Gordon Palmer Hall 505 Hackberry Lane, Tuscaloosa, AL, United StatesTitle: Exact clustering by semidefinite programming under the heterogeneous planted cluster model. Abstract: Clustering, or the sorting of data into groups of similar items, is a fundamental task in machine learning and statistical analysis. Until recently, most computational methods for clustering relied on heuristics with no theoretical guarantee ensuring that clusters present in the data
Applied Math Seminar – Yuhui Chen, University of Alabama
346 Gordon Palmer Hall 505 Hackberry Lane, Tuscaloosa, AL, United StatesTitle: Bayesian Nonparametric Models and Its Applications Abstract: Polya tree priors are random probability measures that are easily centered at standard parametric families, such as the normal. As such, they provide a convenient avenue toward creating a parametric/nonparametric model for data. Briefly, we center a Polya tree at an initial parametric guess on data; then