Hi, my name is

Robert Greathouse.

I build intelligent systems.

I'm a Computer Science student at BYU specializing in Machine Learning. Currently focused on building ML models for baseball analytics and developing tools that empower educators and researchers.

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01.About Me

I'm a Computer Science undergraduate at BYU with a Machine Learning emphasis, maintaining a 3.88 GPA and graduating Summer 2026. My path to tech was unconventional—I worked as a commercial electrician before pivoting to software, giving me a unique perspective on problem-solving and systems thinking.

Currently, I work as a Course Developer and Teaching Assistant under Dr. Gordon Bean, and I recently completed research at BYU's IDeA Lab collaborating with the Texas Rangers R&D team on baseball analytics. My stolen base prediction model achieved 72% accuracy and is under consideration for a paper submission.

When I'm not coding, you'll find me watching baseball (especially stolen base attempts), diving into genealogical research, or exploring new ML techniques.

Technologies I've been working with:

PythonJavaScriptReactJavaSQLscikit-learnPyTorchpandasFlaskGitDockerAWS
RG

02.Things I've Built

Featured Project

Stolen Base Prediction Model

Developed a machine learning model using logistic regression and Bayesian approaches to predict stolen base success probabilities. Achieved 72% accuracy on a model under consideration by the Texas Rangers R&D team. Built comprehensive feature engineering pipeline using Baseball Savant data.

Pythonscikit-learnstatsmodelspandasBayesian Methods

Featured Project

MDXCanvas

Open-source Python library for automating Canvas LMS content creation. Reduced faculty content-creation time by 80-90% and serves hundreds of students. Implements custom MDX parsing and Canvas API integration with comprehensive CI/CD pipeline.

PythonGitHub ActionsCI/CDREST APIs

Featured Project

Baseball Hit Detector CNN

Deep learning project using convolutional neural networks to analyze audio crowd reactions for predicting baseball hit outcomes. Implements transfer learning techniques for improved model performance.

PythonPyTorchCNNTransfer Learning

Other Noteworthy Projects

RepoPilot

Full-stack GitHub assistant application being converted from Python/Flask to Java Spring Boot for enterprise technology experience.

JavaSpring BootReactREST APIs

Audio Baseball Outcome Predictor

ML model using transfer learning to predict baseball outcomes from crowd reaction audio analysis.

PythonCNNAudio Processing

03.Where I've Worked

Machine Learning Research Assistant @ BYU IDeA Lab

Recent

  • ▸Collaborated with Texas Rangers R&D team on baseball analytics research
  • ▸Developed stolen base prediction model achieving 72% accuracy using logistic regression and Bayesian approaches
  • ▸Built comprehensive feature engineering pipeline using Baseball Savant data
  • ▸Contributing to paper being prepared for publication

04. What's Next?

Get In Touch

I'm currently looking for new opportunities in software engineering and baseball analytics. Whether you have a question, want to discuss a project, or just want to say hi, I'd love to hear from you!

Say Hello