I am an undergraduate data science student at Purdue University that loves to take on new problems by analyzing, visualizing, and interpreting data. Specifically, I am interested in the natural language processing subfield of machine learning. In the future, I aspire to be in a role that utilizes classifiers and language models to accurately develop text predictions.
I am building and training a sentiment analysis model of player scouting reports using supervised machine learning. With this sentiment information, I will then predict future contributions for each player and improve accuracy of the player scouting model.
I create videos on examples that help supplement lectures and hold office hours to answer students' questions in the Introduction to Data Structures (CS 251) course. I develop homework, labs, and projects in Python for the Introduction to Data Science (CS 242) course.
I am currently conducting research on the gender pay gap in Dr. Schwab Reese's lab. More specifically, I am analyzing salary data of male and female Ohio State University professors and determining the root causes.
I developed a cross-platform mobile application that expedites the process in which employees check if packages remain in tractor-trailers. I won the Best Intern Award at the UPS Hackathon and was able to present my project to CIO Juan Perez.
I worked in Professor Rafael Lang's laboratory and conducted research on dark matter particles. I compiled a large amount of dark matter waveform image data and retrieved a range of frequencies of where dark matter could exist in Python. I then parsed and cleaned through the data in order to make it usable.
At DemonHacks, the DePaul University Hackathon, my team and I built a web application that allows multiple users to add songs to a music queue using Flask. We won 2nd place at the Hackathon and you can find the code here.
I investigated the gender pay gap of all staff employees at Purdue University in 2018. I then found that the difference between male and female salaries was statistically significant using hypothesis testing and confidence intervals by leveraging R. Finally, I published a Medium article on my statistical findings with data-driven analysis on the root causes of the gender pay gap which you can find here.
My team and I won the 2019 UPS Hackathon by creating a mobile application that scans and tracks QR codes. In this application, we implemented an economically beneficial shipping model that associates a unique QR code with each box.