|2020 Fall (Online) Colloquium and Teaching Seminar Schedule|
|September 30||Colloquium||Padmanabhan Seshaiyer (George Mason University)|
|October 21||Colloquium||Marion Campisi (San Jose State University)|
|November 11||Colloquium||Hadi Susanto (University of Essex)|
|November 18||Colloquium||Jessica Ellis Hagman (Colorado State University)|
|December 2||Colloquium||Luis Sordo Vieira (University of Florida, Department of Medicine)|
Colloquium October 21
Analysis of partisan gerrymandering tools in advance of the US 2020 census
Department of Mathematics, San Jose State University
Over the last decade, mapmakers have precisely gerrymandered political districts for the benefit of their party. In response, political scientists and mathematicians have more extensively investigated tools to quantify and understand the mathematical structure of redistricting problems. Two primary tools for determining whether a particular redistricting plan is fair are partisan-gerrymandering metrics and stochastic sampling algorithms. In this talk I will talk about advantages and limitations of these methods, as well as the legislative and judicial contexts in which these problems exist.
Colloquium September 30
Research and education in computational mathematics for solving real-world problems arising from COVID-19
Professor & Assoc. Dean for Academic Affairs, George Mason University
In this talk, we will discuss how research and education programs can be developed around computational mathematics that will not only help solve several multidisciplinary applications such as those related to COVID-19 but also will help to train the next generation STEM (Science, Technology, Engineering and Mathematics) workforce to solve real-world challenges. Specifically, we will present examples of real-world challenges related to infectious diseases modeled via coupled system of differential equations and present methodologies to solve them using deep learning frameworks. We will also describe how research focus can be integrated with education programs where the primary goal will be to engage students to apply well-developed research concepts in computational mathematics. Incorporating concepts into new or existing inter-disciplinary computational mathematics courses, mentoring students at the graduate, undergraduate and high school level on research projects as well as enhancing pedagogical practices for teachers through professional development workshops will also be discussed.