Won the Gold Award for Impactful Solution, the top prize at Radford's Applied Solutions Showcase, plus a cash prize, for research on how to meet the power demands of next-generation machine learning systems, covering energy sources such as nuclear power and cooling alternatives such as oil in place of water. Presented the findings, "How to Feed AI: An Energy Crisis for the Future," to a panel of industry and academic judges.

Designed and built a serverless task management platform inside Google Workspace, including a distraction-free Focus Mode. Owned the system architecture, wrote the full documentation and diagrams, ran live demos, and refined the tool based on direct user feedback.

Leading an IRB-approved A/B study for Radford's Elevate Research Program, using Cisco Packet Tracer to compare two troubleshooting approaches: evidence-first diagnostics versus immediate AI prompting. Measuring which one gets students to a correct answer faster and more reliably.