Portfolio
Research-driven machine learning work, from graph neural networks to reinforcement learning agents.
During my B.S. in Computer Science, with a minor in mathematics, at Illinois State University, I worked on three machine learning research projects with faculty. Each one meant learning a technique from the research literature and building it myself. The projects covered graph neural networks for materials science and for detecting misinformation, and reinforcement learning for a simulated agent.
Each one links to the project that shows it.
IT 299 Independent Honors Study, ISU
Rebuilt the User Preference-Aware Fake News Detection model from a published research paper. It classifies news tweets as factual or non-factual using graph neural networks and text encoders, drawing on both the tweet’s content and the history of the users who shared it. Training, validation and tuning were automated with MLflow and Optuna. Supervised by Professor Meenal Chaudhari.
MAT 268 Undergraduate Research in Mathematics, ISU
With Joseph Wittrock, trained a virtual spider agent in Unity to follow a moving target without falling over. Presented the poster at the ISU Research Symposium. Supervised by Professor Mehdi Karimi.
Summer project
Used graph neural networks to predict stress forces in materials. Supervised by Professor Mehdi Karimi.
IT 388
MPI and OpenMP versions benchmarked on the Expanse supercomputer: high-performance computing experience. Supervised by Professor Rosangela Fulman.
Graph theory and 3D rendering in Python.
A three-part blog series covering the linear algebra behind quantum circuits.
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