Welcome! Here you'll find a handful of projects that I've worked on during my time at Oregon State.
Master's Project: Studying the Effectiveness of Resnet Structures and Transfer Learning on Convolutional Neural Networks (CNNs)
Completed 05/29/26
In this project I taught myself how to implement neural networks for simple linear regression problems and image classification tasks. I also studied the effects that implementing ResNets and transfer learning techniques had on model accuracy and computation time.
- Read the final report
- Download the model files:
- View the datasets:
Project 2: Wine Quality Analysis Using Machine Learning Techniques
Completed 06/09/2025
This project was one that I did as the final project for ST 599: Topics in Machine Learning. In it, I discuss theory behind machine learning regression techniques, then implement those to analyze wine quality data.
- Read the PDF Report
- View R Code
- View the datasets:
Project 3: Monte-Carlo Simulation Study Involving Low-Probability Events in Golf
Completed 12/10/2025
This is another final project that I did, this time for ST 541: Probability, Computation, and Simulation. This project involved conducting a simulation study to estimate low-probability events, which I chose to apply to the probability of breaking 59 on the PGA Tour.
Project 4: Simulation Study Measuring Effectiveness of Imputation Techniques
Completed 03/20/2026
This project was for a special topics in missing data class that I took. In it, the goal was to use simulated data with varying missingness patterns to quantitatively determine how effective imputation methods were in regression settings.
Project 5: Time Series Analysis: Airline Baggage Data
Completed 03/18/2026
This is a simple project that highlights the application of SARIMA models and their outcomes on some seasonal data from some airlines.