Caroline S Oliver

Caroline S Oliver

Masters Student in Computer & Information Sciences

About

Quick Reference

College of Charleston Class of 2018
B.S. Degree in Data Science with a minor in Computer Science
Overall GPA: 3.8
Magna Cum Laude

College of Charleston & The Citadel Graduate College
Estimated Graduation: Spring 2020
Masters in Computer & Information Sciences
with a focus in Computer & Information Systems

Biography

Caroline is a College of Charleston graduate with a Bachelors of Science Degree in Data Science and a minor in Computer Science. She began her Masters in Computer & Information Sciences at The College/The Citadel in the Fall of 2018 with an estimated graduation of Spring 2020. While getting her masters, she will be working part time to continue development of an application that provides a GUI for the Measurements of Biodiversity in R package, mobr. She is also working to provide automated testing for select mobr package functions.




Skills

Programming Languages

- Java
- Python
- R
- R Shiny
- MySQL
- CloudSQL

Tools

- RStudio
- Excel
- MiniTab
- Google Cloud Platform




Honors


Scholarships

- Willard A Silcox Alumni Scholarship (2014-2018)
- College of Charleston Merit Scholarship (2014-2018)
- College of Charleston Annual Foundation Scholarship (2014-2018)
- Life Scholarship & Enhancement (2014-2018)
- Old Glebe Fellowship (2018-2019)

Honor Society Memberships

- Phi Kappa Phi Honor Society Member as of 2018
- Upsilon Pi Epsilon Honor Society Member as of 2018

Award

- 2018 Outstanding Student Award in the School of Science and Mathematics for Data Science




Experience

NSF REU Computational Genomics, College of Charleston

Summer 2017


Caroline performed a comparative analysis of proteomic and phosphoproteomic data from ovarian cancer patients in R, as well as, worked with a breast cancer database using MySQL, Cloud SQL, and the Google Cloud Platform in conjunction with a doctor at MUSC. She converting the large breast cancer cell line database from CSV files into a SQL database that was to be used in a web application.




High priority alert Prediction & Quantification

Spring 2018


This project completed Caroline's Capstone requirement during her last semester of undergraduate studies at the College of Charleston. A team composed of herself and two addition undergraduate studentsworked with KopisUSA & Vigilix, using their system alert database to predict if a store qualified as a high frequency alert store, as well as, quantify the probability for a repeat alert for a given time interval.




Author of the Measurements of Biodiversity in R (mob-r) Application

Spring 2018 to Present

mobr_app GitHub repo


Caroline has had the wonderful opportunity to pair with Dr. Dan McGlinn and the mob-r team of collaborators, to create a graphical user interface for the R package mob-r using R shiny framework. This application features various biodiversity calculation functions, such as rarefaction, abundance, mob metrics, & delta statistics, and allows for dynamic parameter selection which allows the user to customize the functions to meet their specific calculation needs without having to use or see any of the r package code.




Test Developer for the mobr Package

Spring 2018 to Present

Testing files on GitHub


Working with Dr. McGlinn and the mob-r team once again, Caroline helps to develop a testing suite for various the mob-r functions that are altered and/or optimized at a greater frequency. These test assure that any changes to the functions can be tested quickly and accurately by members of the mob-r team to help streamline the package development process.