Continued working on computer vision projects as a Computer Vision Intern

Develop and utilize computer vision and control algorithms to enable high-speed testing of semiconductors and thin film materials. Implement algorithms for real-time object detection, recognition, and tracking. Design, implement, analyze, and optimize novel algorithms for next-generation metrology systems.

Implement data clustering methods by comparing different clustering methods and integrating them with existing software tools in the MATLAB GUI to reduce estimation error rates during data recovery.

Worked with professor Franklin in ECSE 2500 Engineering Probability.

Utilized Python to effectively extract, process, and integrate diverse product information, enabling the generation of specialized data tables for different product managers and ultimately augmenting work efficiency by 99%. Moreover, I spearheaded the development of a Python-based web searching application, providing real-time tracking of various product processes. This critical tool served to streamline usability tests, offered optimization strategies, and foresaw potential usability patterns, significantly enhancing the overall product development cycle.