Grad student at George Mason, curious about how AI is changing education and what data can tell us about the systems we learn in. I like building things, breaking things down to understand them, and figuring out how technology intersects with real people's lives.
Designed and analyzed a communication system for emergency scenarios where normal infrastructure fails. The interesting part was layering multiple analysis frameworks on top of each other — using PASTA for threat modeling, STRIDE for attack surface mapping, and LINDDUN for privacy risks — then pulling it all together into one coherent picture of what could go wrong and how to fix it.
Built classification models to predict diabetes likelihood using the Pima Indians dataset. This was my first deep dive into the full ML pipeline — cleaning messy health data, engineering features, training and comparing models (Logistic Regression, Naive Bayes, SVM), and thinking about what it means to use algorithms for decisions that affect real people.
Deep dive into a research system that uses millimeter-wave radar to detect and reconstruct sound from object vibrations — no microphone needed. I analyzed the signal processing pipeline, the deep learning components, and spent a lot of time thinking about the privacy and surveillance implications of technology like this.
Always open to conversations about research, interesting problems, or just saying hi.