Hello! I am a recent grad student from Oregon State University, where I obtained my MS in Artificial Intelligence. I had started my journey at Sierra Community College in 2015 as a Business major, eventually switching to Accounting, and then Computer Science, and finally transferring to Chico State in the Fall of 2019. While at Chico I completed my B.S. in Mathematics (Statistics focused) and a minor in Computer Science, graduating in May 2022. Following this I continued my education into grad school to study in the field of Artificial Intelligence, and recently graduated in June 2024.
Outside of my education I mainly focus on developing skills in machine learning, applying both what I learn in class and on my own. I’ve worked on projects including image classification of brain tumors, stroke prediction using statistical modeling, and regression modeling for predicting food production needs.
During my time at Chico State, I worked at the Center for Healthy Communities as an Undergrad Research Assistant and Community Health Assistant. The main focus of my work had been being the lead programmer on a series of integrated scripts to manage administration and compensation for a multi-site health survey. I have also worked on revising the BNS3 website I built during my research program (see blog post for more information) in order to prepare it for publication.
During my time at Oregon State, I worked as a Graduate Teaching Assistant (GTA) in the EECS department where I assisted in courses such as: Computer Architecture & Assembly Language (CS 271), Design Engineering & Problem Solving (ENGR 102), and Engineering Computation and Algorithmic Thinking (ENGR 103). I applied my knowledge in a 9 month project (Non-Thesis) in which I collaborated with Washington State University to implement methods for Automated Quality Control for Weather Stations via Historical Data (see blog post for more information).
Thank you for taking a look at my website and I hope you find something you enjoy!
The research paper produced from my 9 month capstone project (Non-Thesis) as part of my MS in Artificial Intelligence, focused on developing methods for applying QC on weather station data.
An ethical analysis of Large Language Models (LLMs) in US Healthcare, as part of a term long paper in PHL 546: Social and Ethical Issues in Artificial Intelligence.
A general introduction to working with databases and the GC Platform, implemented through various projects in the graduate course CS 512: Data Science Tools and Programming.
This project deals with estimating the parameters for the Polya’s distribution, specifically the: Fisher Information Matrix, Cramer-Rao Lower Bound, Maximum Likelihood Estimator, and Method of Moments.
In this project, problematic data is utilized with various machine learning models. Multiple solutions to these challenges are explored and results are compared to discover the best methods.
The final product of my summer Undergraduate Research Program and partially into my work as a Data Science Intern, the BNS3 website has been published to present findings from the pilot 2 survey.