Selected as sole CS major for a $10,000 fellowship to advance hardware security research. Collaborating to generate circuitry diagrams from electron microscope images, aiming to detect potential alterations in integrated circuits within the semiconductor supply chain. @ Secure and Trustworthy Hardware (SETH) Lab.

Developing a ML-based, non-invasive glucose monitoring solution using biosignal metrics. My role spans data preprocessing, feature engineering, and model optimization. @ Perception, Sensing and Instrumentation (PSI) Lab

• Created data-driven dashboard to track student progress• Maintained strong customer relations, ensuring our services align with educational objectives.• Managed the branch's budget, marketing, and resource allocation.

• Automated contamination labeling in Yieldstar optical metrology sensors with CV, reducing labor time by 95%• Discovered and proposed optimizations for Yieldstar C# validation tests, projected to save $2.4M annually• Developed multiple Python scripts, reducing test report processing time from 295 hours to 9 minutes (99.9% improvement)• Collaborated on multi-department workflow standardization web app, enhancing efficiency across teams through MS Teams Adaptive cards/Emails• Contributed towards standardizing mature software development practices within Production