Computer science student, software engineer, researcher, and occasional writer.
I build software, work on research, and write about things I find interesting.
Things I'm learning, working on, and thinking about.
The first article is on its way.
Where I have worked on open questions.
Studying what EEG-to-text decoding really recovers from a brain signal, and whether individuals can be re-identified from their recordings across sessions, devices, and datasets.
Read research →A reproducible simulation framework comparing five event-triggered acoustic-monitoring policies under embedded memory and power constraints.
Read research →Joining an ongoing collaboration that audits and corrects baseline vessel-size classifiers on the AI4Shipwrecks side-scan sonar dataset.
Read research →Selected work, research, and study.
Expected graduation May 2027. GPA 3.74/4.0.
Later elected President, a role I hold from Spring 2026.
Led a 3-person team building native iOS apps in Swift and SwiftUI.
Event-triggered acoustic monitoring for TinyML. I led the three-person project.
A retrieval-augmented helpdesk prototype built with a team of three. It was a prototype and was not deployed.
Studied the security and privacy of EEG brain-signal decoding under Dr. Nick Rahimi.
Continuing EEG security research with Dr. Ahmed Sherif.
An archive of things I have built.
A proof of concept for the Mississippi Department of Public Safety that cross-checks recorded interrogation statements for contradictions, with every flag traceable to its source statement, speaker, and timestamp.
A retrieval-augmented IT helpdesk prototype for the Mississippi Development Authority, built with the Mississippi AI Innovation Hub and selected at the statewide AI showcase. It was a prototype and was not deployed.
A simulation framework that compares event-triggered recording policies for acoustic monitoring under embedded memory and power limits. Presented as a poster at the USM Undergraduate Research Symposium.
Five machine-learning classifiers trained on CICIoT2023 (508K instances, 34 attack types), with SHAP feature attribution and noise-robustness tests.
A cross-platform app that keeps music playback in sync across devices over WebSockets, using timestamp-based drift correction.
A native iOS reading app for EPUB, PDF, and TXT with AI-generated chapter summaries, highlights, bookmarks, collections, and reading stats.