Loyola University Chicago

Mathematics and Statistics


Undergraduate Research Symposium

Undergraduate Research Symposium

Undergraduates presenting their research during the Weekend of Excellence Poster Session.

Congratulations to all of the Math and Statistics majors that presented at the Undergraduate Research Symposium, which took place April 16th in Mundelein Hall. Our majors participate in research throughout many disciplines - take a look at their projects from the Weekend of Excellence below!

1) Analysis of Optimal Poker Strategies - Kaitlin Parsons, Mathematics (2017)

Mentored by Peter Tingley, Mathematics

Is it a good idea to bluff? One way to think of this concept is as follows: Is it a good idea to bluff assuming your opponent is a good player and knows your strategy and knows that you will bluff on certain hands? Each player has an optimal strategy. That is to say, each player has a strategy once implemented, will cause the opponent to have no better option. By analyzing small games, we are able to see certain patterns of optimal strategies that hold true for even more complicated games.


2) Application of Jones Calculus to Specialized Cell Geometrie - Justin Stuck, Theoretical Physics and Applied Mathematics, Mathematics (2017)

Mentored by Robert Polak, Physics

Maltese cross patterns have been observed using polarized microscopy along the edges of E.coli cells and droplets of crude oil immersed in water. To understand the optical effects of these specialized geometries, we have developed a model with a layer of anisotropic birefringent material encapsulating an isotropic center with the extraordinary axis of the anisotropic media perpendicular to the surface. Jones matrices are utilized to represent the passage of the polarized light through the model and the results are calculated numerically using MATLAB and analytically. The results are compared with each other and closely correspond to observation.


3) Site-directed Mutagenesis, Expression and Purification of Various Mutants for ADP-Glucose Pyrophosphorylase from A. tumefaciens and E. coli - Laura Gonzalez-Martin, Mathematics (2017)

Mentored by Miguel Ballicora, Chemistry

ADP-glucose pyrophosphorylase is a regulatory enzyme in the pathway that produces glycogen in bacteria and starch in plants. ADP-Glc PPase catalyzes the first committed step in the synthesis of these storage polysaccharides via the formation of ADP-glucose. This enzyme is allosterically regulated and catalyzes the conversion of ATP and glucose-1-phosphate to ADP-Glc and inorganic pyrophosphate. A specific amino acid residue hypothesized to play a key role in a binding site was replaced using site-directed mutagenesis. The enzyme was then expressed and purified for kinetic assays to determine the effect of the mutation on binding affinity and ADP-glc synthesis.


4) Purchasing Power of Peace: Effects of Business on International Conflicts - Colin Williams, Mathematics (2017)

Mentored by Molly Melin, Political Science

In a globalized world, non-state actors become increasingly influential in the political sphere. Corporations are no exception. This research takes on an emerging area of conflict management research, seeking to demonstrate the potential effects corporations have on their areas of operation. Through information obtained from various standing conflict databases as well as newly collected data, this project has produced some of the first quantitative analysis on the role of businesses in conflict management and peace processes.


5) Deferentially Expressed Genes From Diet Induced Obesity - Shyam Shah, Bioinformatics and Statistics (2017)

Mentored by James Cheverud, Biology; Madeline Keleher, Biology

The goal of this project is to investigate the intersection of obesity, diet, and gene expression. Specifically, I plan to find differentially expressed genes from mice that were given either a low fat, or a high fat diet. The RNA-Seq data of these mice will be analyzed against specific phenotypes that were measured such as insulin tolerance, glucose tolerance, leptin levels, cholesterol levels, and liver weight. For analysis I will use R, and the R package WGCNA. I will create clusters of genes correlated with desired phenotypes. Then the genes, and their clusters will be analyzed with multiple databases.