Instructor of record for STOR 113, STOR 120, STOR 155, STOR 320, STOR 455, STOR 390

This position has thus far entailed two semesters of experience in STOR 538 (sports analytics). This is an upper-level statistics course aimed to provide juniors and seniors within the Statistics department with project-based analytical skills. Outside of holding weekly office hours designed to reinforce and clarify the lecture, I am tasked with grading projects as well as designing the mid-term project. In my first semester I scraped NFL data from the 2020 season. This data was strategically left “unclean” so as to encourage students to practice not only their forecasting and modeling skills, but also necessary data preparation techniques. Ultimately students forecasted the following week’s “outcomes” ranging from a specific game’s winner, to the over-under line, and margin of victory.

I am researching the effects of peer assisted tutoring on historically challenging classes at Clemson University and Tri-County Technical College. I coordinate with the Clemson Supplemental Instruction department to advise the best allocation of resources.

I am doing work on asynchronous computational modeling of the immune system. I will be implementing code in Erlang and ZeroMQ to build network structures analogous to the communication methods of nodes in the immune system.

Clemson Supplemental Instruction partners with Tri-County Technical College and the Clemson Bridge program to provide students with an added resource to navigate through historically difficult classes. Over the past two semesters I have walked students through calculus one, but I also am looking forward to also tutoring calculus two, three and physics. The SI program provides the unique opportunity to work with a diverse group of students. From the traditional 18-22 year old college student, to a 16 year old high school student taking a duel-credit math course, to a 43 year old mother of two going back for her degree, I have to be flexible and accommodating in my methods of communication to be able to mentor to all of these varying students.

This was joint work with the Harvey Mudd department of social science. Our aim was to discern propensity to bicycle as an alternative form of transportation (particularly commuter transportation) within the greater Los Angeles area. Beyond designing protocol for efficiently collecting survey data in a diverse population, our team was tasked with deriving a logistic regression model. As is often the case, mode selection was key when balancing the competing interests of predictive accuracy and covariate explanatory power.

I am doing research in realistic contact networks in epidemiology. The conventional model for going about epidemiological research has been to model human interaction through a series of ordinary differential equations. However, this oversimplifies the system by assuming that human interaction is static when it is fact dynamic. Hence the need for contact networks that more accurately capture the ebb and flow of human interaction to provide a more comprehensive model for the spread of communicable disease.