Mathematics and Computer Science Seminars

The Mathematics and Computer Science Seminar topics range widely, but typically focus on original research, technical exposition, snapshots of working life, or teaching.

Seminar Schedule (Fall 2019 - Spring 2020)

Seminar attendees are invited to gather at 15 minutes prior to the talk to partake of light refreshments and to socialize.

9/23, 2019

Opportunities in Math, CS, and Physics

David Latimer (physics), Jake Price (math), Adam Smith (CS), and Courtney Thatcher (math)

University of Puget Sound

4pm, Thompson 395

 

Are you interested in summer programs in math, CS, or physics but don’t know where to start? Would you like be more involved during the semester but don’t know what activities exist? Are you interested in graduate school but don’t know how to prepare? Do you wonder what jobs are available after you graduate? Come to the first talk of the semester and hear about opportunities in math, CS, and physics. There will be plenty of time for questions, too.

10/14, 2019

An Introduction to Configurations, k-Configurations, and Superconfigurations
Benjamin Peet
Department of Mathematics

St. Martin’s University

4pm, Thompson 395

 

This presentation will begin by exploring the definition of a configuration of points and lines. That is, an arrangement of points so that: 1) no pair of points are on more than one line, 2) each point is on the same number of lines as any other, and 3) each line has the same number of points. We will then proceed to an investigation of what an extension to a "configuration" of points and planes
might look like. These will be referred to in general as k-configurations. Finally, the notion of a superconfiguration of points, lines, and planes is introduced, where the points and lines form a (1-) configuration; the lines and planes form a (1-) configuration; and the points and planes form a 2-configuration. A number of examples will be presented throughout as well an exploration of the computational aspects of finding configurations and their automorphism groups.

11/4, 2019

A Glimpse into Machine Learning at AWS
Chris Swierczewski
Amazon Web Services

4pm, Thompson 395

 

What is it like to be a scientist at Amazon Web Services? In this talk I will share my experience at AWS through a wide variety of problems I have worked on, showing that there is more to working in machine learning than just neural networks. I will begin with a broad overview of the kinds of problems worked on by scientists all across AWS. Then, I’ll dive into three problems I worked on, personally. The first is the use of tensor decompositions to do topic modeling, a subfield of natural language processing. Second, is an anomaly detection algorithm based on using trees for density estimation. And third is using graphs and clustering to improve upon K-nearest neighbors search. 

11/11, 2019

Different difference quotients (Finite difference: from PDEs to computer vision)
Yajun An, Ph.D.
University of Washington Tacoma

4pm, Thompson 395

 

We have all learned derivatives and their difference quotient definition in differential calculus. Now with the help of computer algorithms, we can do a lot of cool things with them. In this talk, we will explore some of their applications, including simulating waves, detecting edges in a digital photo, and more. We will show a couple of examples of each application.

2/3, 2020

Bias in Algorithms and the Misuse of Big Data Sets
Henry Walker
Visiting Professor of Computer Science, University of Puget Sound

4pm, Thompson 395

 

The news abounds with stories about the uses of algorithms and Big Data. In this reporting, successes are widely publicized. However, discussion of bias and challenges is spotty at best. In many settings, it seems that policies and practices may assume that computing algorithms will be unbiased and objective, and results are not challenged.

 

And yet, a March 23, the subtitle of a 2019 story in the Wall Street Journal proclaimed, "Data scientists and civil rights groups are raising the alarm about bias in algorithms that determine everything from who goes to jail to how much your insurance will cost". Also, the subtitle of Cathy O'Neil's book, "Weapons of Math Destruction", highlights, "How Big Data increases inequality and threatens democracy."

 

This talk will review a range of issues and challenges in deployed computing systems and encourage all to consider the appropriate role of technology in the setting of both policies and practices.

2/17, 2020

Stable or unstable? What it means, why we care, and how we figure it out.
Jeremy Upsal, PhD Candidate
University of Washington, Seattle

4pm, Thompson 395

 

Abstract: Differential equations are used to model situations where one dependent quantity changes as another independent quantity changes. When the independent variable is time, this is called a dynamical system. Equilibrium solutions of dynamical systems are solutions of the differential equation that stay put as time changes. An example of this is a pendulum in the resting position: the pendulum does not move as time goes on. This resting pendulum is an example of a stable equilibrium solution of the differential equation since if you poke it, the pendulum stays near the equilibrium solution. In this talk we will talk about the physical definition of stability, the mathematical definition of stability, and how they coincide. We will start by talking about equilibrium solutions of Ordinary Differential Equations and then talk a little bit about how it works for Partial Differential Equations. Most of this talk should be accessible to those who have taken Calculus.
 

3/2, 2020

Making Juggling Mathematical

Eric Tou
University of Washington, Tacoma 

4pm, Thompson 395

 

Abstract: Juggling has a long history, dating back over 3,000 years. During most of this long history, juggling was the avocation of entertainers and artists. Only in the 1980s was a method developed to keep track of different juggling patterns using a numerical code, now known as a siteswap. This numerical shorthand gives rise to a set of integer-like objects that can be analyzed using number-theoretic techniques. We'll explore some key results in the mathematics of juggling and consider how to use analytic methods to approximate the number of "prime" juggling patterns of a certain type.

4/13, 2020

TBD
Allison Henrich
Seattle University

4pm, Thompson 395