WSU Vancouver Mathematics and Statistics Seminar

WSU Vancouver Mathematics and Statistics Seminar (Spring 2017)


Welcome to the WSU Vancouver Seminar in Mathematics and Statistics! The Seminar meets on Wednesdays at 1:10-2 PM in VUB 107. This is the building marked "N" in the campus map, and all Math/Stat faculty have offices in this building. The seminar is open to the public, and here is some information for visitors.

Students could sign up for Math 592 (titled Seminar in Analysis) for 1 credit. Talks will be given by external speakers, as well as by WSUV faculty and students. Contact the organizer Bala Krishnamoorthy if you want to invite a speaker, or to give a talk.

Seminars from previous semesters


Date Speaker Topic Slides
Jan 11     canceled due to snow
Jan 18     intro, coordination
Jan 25 Matthew Sottile, Sailfan & WSU Opinion dynamics models based on interaction potentials with topic coupling

Abstract (click to read)

Opinion dynamics models are used to reason about the transmission, change, and stability of opinions within a population of agents. The core components of such a model are the mechanism for modeling interaction and the mechanism for updating the opinion held by agents after interaction. Models of such systems date back to the 1950s and continue to be studied today. Their applicability ranges from the study of social dynamics of humans to interactions in synthetic systems such as distributed agent based-ones in which the concept of "opinion" maps to one or more state variables that are updated during agent interactions.

This talk will present ongoing research work that involves the creation of a generalized framework for opinion dynamics models based on interactions represented via potentials, with opinion updates based on the minimization of all possible interactions within the population. We have shown that existing linear models can be represented in our framework. Furthermore, we can represent models that capture dynamics that cannot be represented by prior models. Finally, we also introduce a new concept of opinion coupling that has not been well studied or modeled.

This work is a joint effort with Hossein Noorazar (WSU PhD student) and Kevin Vixie.

Slides
Feb   1 Bala Krishnamoorthy, discussion Tips for creating an effective job resume
Feb   8     No seminar
Feb 15 Leslie New, WSU A brief introduction to science communication

Abstract (click to read)

Being successful in science is about more than just doing good research. It also requires that individuals be able to communicate their research to others. There are multiple ways to communicate science, from peer-reviewed journals to popular science articles to radio interviews and more. We will focus our discussion on oral presentations, addressing habits that make for effective speakers as well as some tips for slide presentation. While practice may make perfect, starting with good habits will help you reach perfection that much faster.

Feb 22 Safia Chettih, Reed College Topology of Configurations on Trees

Abstract (click to read)

Configuration spaces of graphs have a rich network of connections to many areas of mathematics, while some basic properties of these spaces elude a general description. This talk will introduce some fundamental tools of algebraic topology that help to understand better these configuration spaces, and touch on a discretized model for configuration spaces of graphs which has made deeper insights possible. I will show how the homology of configurations on trees can be completely understood via configurations on subtrees, and give concrete examples of the homology classes we might see.

slides
Mar   1     No seminar
Mar   8 Bala Krishnamoorthy Image correspondence recovery via binary quadratic programming postponed

Abstract (click to read)

We consider the problem in computer vision of matching features in a set of images. We are given pairwise similarities (or affinities) for sets of image features. Our goal is to find sets of matching features which explicitly satisfy cycle consistency across multiple images. We propose an approach based on binary quadratic programming. Our main insight is that using a series of carefully chosen relaxations of the binary quadratic variables into binary variables, the problem can be cast into a linear program that could be tackled by existing solvers. This is ongoing joint work with Sudipta Sinha from Microsoft Research.

Mar 15 Spring break; no seminar
Mar 21 Sergey Lapin, WSU Mathematical modeling of ocular blood flow (VUB 221, 4:10-5 PM)

Abstract (click to read)

Open angle glaucoma (OAG) is the second leading cause of blindness in the world, and is characterized by changes in the optic nerve head and retinal ganglion cell death, resulting in irreversible vision loss. The lack of understanding of the roles of various risk factors in OAG constitutes a major limitation in the diagnosis, management, and treatment of OAG. One of the known risk factors for glaucoma is elevated intraocular pressure (IOP). Mathematical modeling offers an important tool for understanding the relative influence of risk factors by linking the mechanical action of IOP on ocular tissues to the blood flow and oxygen transport within the ocular tissues. The main objective of this work is to study the relationship between intraocular pressure, blood pressure, and blood flow autoregulation in the retinal vasculature, and develop mathematical models that can be used to model conditions specific to individual glaucoma patients.

slides
Mar 27 Yuan Wang, WSU Functional data analysis for dynamic CT imaging (VUB 126, 12:10-1 PM)

Abstract (click to read)

Functional data are often generated when diseases features are accessed repeatedly over time and at multiple spatially interdependent units. The problem is motivated by a liver cancer study where patients underwent a dynamic computed tomography (CT) protocol to enable evaluation of multiple perfusion characteristics. The study was undertaken with the objective of determining the effectiveness of using perfusion characteristics to identify and discriminate between regions of liver that contain malignant tissues from normal liver tissue. To reduce model complexity and simplify the resulting inference, possible spatial correlation among neighboring units is often neglected. In this work, we consider a multivariate functional data model and propose a modified kernel smoothing estimation to leverage the spatial and temporal correlation. We also address the companion problem of developing a simultaneous classification method that that utilizes the inter-unit correlation information to predict disease state. The proposed method outperforms conventional functional data classification approaches in the presence of strong correlation. The method offers maximal relative improvement in the presence of temporal sparsity wherein measurements are obtainable at only a few time points.

Apr   5
Apr 12 Mau Nam Nguyen, Portland St.
Apr 19
Apr 26

Last modified: Sun Mar 19 23:11:18 PDT 2017