• Architected and developed TissueSense, a laboratory automation platform in Python (CustomTkinter, MVC) that integrates control of tunable lasers, precision stages, a 6-axis robotic arm, fluidic systems, and microscope cameras for automated biosensing workflows.

• Engineered an auto-alignment system using Archimedean spiral search with adaptive step sizing and real-time power optimization, with heatmap visualization and CSV export for post-analysis.

• Built well plate and wafer scanning modules supporting 96/384-well plates, custom plates and custom PIC coordinate sets, with per-well spectral acquisition, auto-alignment, and real-time scan monitoring.

• Built and maintained internal applications across multiple departments, supporting engineering, production, and business operations

• Designed and implemented new C# features for optical coating software, enhancing design accuracy and reducing production errors by 20%.

• Automated repetitive engineering tasks using Iron Python scripts, reducing manual work by 30% and saving engineers an average of 5-6 hours per week.

• Make all physical preparations for areas within buildings where the event is requested

• Move furniture and store or stack it as required

• Setup chairs, tables, coat racks, curtains, and stations

• Clean the bleachers in the Clark Gym and take up floor coverings in the Clark Gym

• Developed and maintained Python-based software for lithium-ion battery analysis,

integrating Matplotlib, PyQT5, and Pandas, resulting in a 20% improvement in data visualization accuracy.

• Collaborated with battery engineers to validate application data, ensuring 100%

compliance with program specifications and improving calculation precision by 15% on average.

• Led a team of 3 software co-ops, acting as the primary contact for troubleshooting and support, resolving 90% of inquiries and reducing downtime by 25%.