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# Graduate Student Seminar

**DMS Graduate Student Seminar**

Jan 09, 2019 03:00 PM

Parker Hall 249

**organizational meeting** followed by

**Dr. Abebe** presenting a brief overview of his own research.

**DMS Graduate Student Seminar**

Dec 05, 2018 03:00 PM

Parker Hall 249

Speaker: **Gopal Nath** (Gopal is a PhD student in our department, specializing in statistics; his advisor is Dr. Ash Abebe.)

Title: Amboseli Elephant Population Dynamics Using Integral Projection Models

Abstract: The most commonly used data-driven models for population dynamics are matrix projection models (MPM), which project discrete population structure (age or size classes) in discrete time. IPMs are analogous to a matrix projection model with a constant matrix and constructed from general regression models predicting vital rates from state variables (e.g. mass, size or age). In our study, we will introduce the basic concepts underlying IPMs, and step through the complete process of building, and then an IPM based on population studies of Amboseli elephants is used to analyze their population dynamics.

**DMS Graduate Student Seminar**

Nov 28, 2018 03:00 PM

Parker Hall 249

Speaker: **Jasmine Betties**, Ph.D. student in Educational Psychology and Graduate Student Ambassador

Presentation/workshop: Individual Development Plan (IDP): a strategic plan for graduate students to first assess their strengths and weaknesses, then set goals and map a plan to accomplish them.

For more information, see http://graduate.auburn.edu/current-students/professional-development/individual-development-plan.

**DMS Graduate Student Seminar**

Nov 14, 2018 03:00 PM

Parker Hall 249

Speaker: **Serhat Simsek**, a PhD student in our department, specializing in statistics; his advisor is Dr. Mark Carpenter.

Title: Do Analysts Mislead Medical Practitioners? A Comprehensive Analytics Technique to Better Detect Non-Surviving Cancer Patients

Abstract: Analysis of survival times of cancer patients is crucial for medical practitioners to determine possible outcomes and make better future-plans for the patients. In the healthcare analytics literature, it is common to see employment of machine learning algorithms to predict survivability of the cancer patients. In this study, we detected the common misleading methodology that has been used in the literature in predicting the surviving and non-surviving cancer patients and propose a comprehensive modeling technique that overcomes the issue of the misprediction of survival. In order to illustrate the issue and its solutions, we deploy Artificial Neural Networks, Random Forest and Logistic Regression. The comprehensive model is applied to rectum cancer data and results are validated with breast cancer data from the SEER. The results will assist medical practitioners to make better decisions for their patients and thus appropriate interventions.

**DMS Graduate Student Seminar**

Nov 07, 2018 03:00 PM

Parker Hall 249

Speaker: **Dr. Guanqun (Vivian) Cao**, Associate Professor of Statistics

Title: Nonparametric regression model for high-dimensional data

Abstract: In this talk, I will briefly introduce several popular nonparametric regression models and their application in high- dimensional data analysis. My recent works on functional data analysis will be presented.

**DMS Graduate Student Seminar**

Oct 31, 2018 03:00 PM

Parker Hall 249

Speaker: **Dr. Sheng Bau**, visiting professor from the University of Kwazulu Natal in South Africa.

Professor Bau will present the second part of his two-lecture introduction to TeX, the default type-setting software for mathematicians and statisticians around the world.

Title: TeX and LaTeX

Abstract: I thought this could be useful to the graduate students or anyone who has an aim of production of high quality typesets of an article, a thesis, a report, a letter, or a presentation. The first talk will be followed, if I may be permitted, by a second talk that is slightly more advanced.

**DMS Graduate Student Seminar**

Oct 24, 2018 03:00 PM

Parker Hall 249

Speaker: **Dr. Sheng Bau**, a visiting professor from the University of Kwazulu Natal in South Africa.

Title: TeX and LaTeX

Abstract: I thought this could be useful to the graduate students or anyone who has an aim of production of high quality typesets of an article, a thesis, a report, a letter or a presentation. The first talk will be followed, if I may be permitted, by a second talk that is slightly more advanced.

Professor Bau has agreed to give two talks in the seminar (this week and next), providing an introduction to TeX, by now the default type-setting software for mathematicians and statisticians around the world.

**DMS Graduate Student Seminar**

Oct 17, 2018 03:00 PM

RBD Library

This week's meeting will be at RBD Library.

**Patricia Hartman**, math & stat liaison at the library, will introduce library resources available to graduate students. Details TBA.

**DMS Graduate Student Seminar**

Oct 03, 2018 03:00 PM

Parker Hall 249

Speaker:

**Professor Douglas Leonard**

Title: Using Computer Algebra Systems to Test and Improve Mathematical Theory

Abstract: I will show examples of how I use Computer Algebra Systems (Macaulay2, Singular, and Magma) to try to understand mathematical theory, test it, and improve it. These examples may be about integral closures of rings or ideals, or desingularization of function fields, but the takeaway is how completely understanding small but non-trivial examples is important in shaping theory.

**DMS Graduate Student Seminar**

Sep 26, 2018 03:00 PM

Parker Hall 249

Speaker: **Daryl Granario**, a doctoral student who is completing his dissertation under Professor Emeritus Tin-Yau Tam.

Title: Matrix decompositions and canonical forms

Abstract: The problem of writing a matrix into a product (or sum) of special types is at the core of linear algebra and matrix theory. We look at classical decompositions and give more general factorizations using the theory of canonical forms and other techniques in matrix analysis.

Last Updated: 09/11/2015