Welcome to my academic website! My name is Shelby Scott and I am currently Health Data Scientist for Guidehouse. By trade, I consider myself to be a biomathematician and biostatistician, but I have experience in a variety of different fields. Feel free to explore my talks, publications, and other tabs to learn more about my research.

If you’re here from my SMB talk, welcome! If you are interested in seeing the slides, find them on my SMB 2022 page! Also, in case my talk needs some spicing up, play some Seminar Bingo. If you’re interested in the book mentioned in my talk, buy it here.

Background

I received my B.S. in Biomathematics from Rhodes College in Memphis, TN, in 2015 under the advising of Erin Bodine. My love of research began in the fall of 2012 when I enrolled in a mathematical modeling course focusing on disease dynamics using ordinary differential equations. From there, I was doomed in the best way possible. The next summer I participated in a Research Experience for Undergraduates (REU), which focused on the Santa Cruz Island fox and the potential reasons for its population decline in the 1990s. This resulted in a number of talks and two publications.

Following graduation, I immediately enrolled as a PhD student in the Department of Ecology and Evolutionary Biology (EEB) at the University of Tennessee, Knoxville (UTK), advised by Dr. Louis J. Gross. At UTK, concurrently earned a MS in Statistics through the Interdepartmental Graduate Statistics Program (IGSP). My dissertation used mathematical and statistical models to observe and predict the epidemic spread of gun crime in Chicago, Illinois.

Graduate Work

I was a student under Dr. Louis J. Gross working in cellular automata modeling. In systems like wildfire, infectious diseases, and social epidemics, it is important to understand the spatio-temporal spread of these processes and the associated dynamics. Cellular automata models are composed of a lattice of cells, each existing in a specific state. Over time, local rules determine how the states of the cells update. We can then look at how these rules influence the dynamics of the system.

For a number of these systems, it is also important to determine how to optimize and control a specific system. Unfortunately, there is not an extensive literature on how to optimize or control spatio-temporal models. Part of my work also looked at the existing methods to carry out these studies and potential other means of optimizing and controlling spatio-temporal spread.

Spatio-temporal models are often improved with the incorporation of data. Another part of my work used statistical models to determine which factors are most appropriate to incorporate into these mathematical models to best represent the system. Particularly, I use Bayesian statistics to answer these questions.

Current Work

In May of 2021, I started a job as a Senior Consultant at Guidehouse. Guidehouse is a federal and commercial consulting firm out of Washington, DC. My main work is as a Health Data Scientist, applying my mathematical and statistical skill set to interesting client questions.

The Advanced Analytics and Intelligent Automation team is a leader in AI and automation across the public and commercial sectors with numerous publications, awards, and top honors in government-wide data science challenges. My team serves as a trusted partner and guide to senior leadership, supporting client challenges from intelligent automation to artificial intelligence and machine learning.