Summer Research Symposium

Summer Research Symposium – Oral Presentations
Friday, September 26, 3:20-5:00pm, Carver Science

The symposium will start with everyone gathered in Jordan Lecture Hall for the Welcome and the first presentation.  The remaining presentations will be held concurrently.  Audience members will have time to switch rooms between presentations.

Carver 215 (Jordan Lecture Hall)

Carver 231

Summer Research Symposium – Poster Presentations
Friday, October 3, 3:30-4:30pm, Carver Science Atrium


Abstracts: (additional abstracts coming soon)


Geoff Converse, Jared Grove, and Kylie Pape
Dr. Albert H. & Greta A. Bryan Summer Research Program – Simpson College
Maximizing Potential in a Fantasy Football Draft
In a fantasy sports league, the draft is the first opportunity for team managers to gain an advantage over their opponents.  We created a computer program in R that can maximize a team’s projected value gained from a fantasy football draft.  The key feature of our program is its ability to predict when players will be taken in future rounds.  This enables our team to draft the best players being considered by opposing teams in a given round and also draft players before there is a drop in value at a given position.  Our program is able to learn the strategies of opposing teams as the draft progresses and therefore adjust its predictions for future rounds to increase its accuracy.  Thus, even when our program starts with very little knowledge of the strategies used by the competing teams, it is able to finish with a competitive edge.  We completed this project during the Dr. Albert H. & Greta A. Bryan Summer Research Program in Mathematics at Simpson College.

Sara Reed with Levi Boxell (Taylor University), Yihang Du (Lafayette College), Dr. Jeffrey Liebner (Lafayette College), and Dr. Julie Smith (Lafayette College) 
Summer 2014 REU in Mathematics/Economics – Lafayette College in Pennsylvania
Finding NAIRU
The non-accelerating inflationary rate of unemployment (NAIRU) is a fundamental concept in macroeconomics. Defined as the rate of unemployment at which the inflationary rate does not change, NAIRU is widely used by policymakers to help determine fiscal and monetary policy. However, NAIRU presents a challenge in that one cannot directly observe NAIRU in the same manner that one can observe the unemployment rate. This challenge also makes it difficult to determine how accurate one’s estimates of NAIRU are. In our approach to estimate NAIRU, we employ various univariate smoothers and filters in order to extract the underlying trend from the cyclical unemployment rate. We also use a state-space model and the Kalman Filter along with an EM Algorithm to extract the unobserved state of NAIRU. We expand upon current methods used to estimate NAIRU by utilizing a more general multivariate autoregressive state-space model (MARSS) that incorporates structural changes in the labor market. When assessing the predictive ability of our estimates of NAIRU using the Phillips curve, we find that our estimates perform as well or better than those provided by the Congressional Budget Office.

Rachel Rice
Marshall Space Flight Center – NASA
Dayside Aurora Modeling

Click here for the Fall 2013 program.

Click here for the Fall 2012 program.