Developed fulfillment automation software supporting Amazon's grocery businesses.

• Led a team of 9 undergraduates developing waypoint and obstacle detection software• Responsible for the integration of computer vision software with mechanical and electrical systems and presentation of subteam project plans to MRover advisory board• Designed and implemented innovative software that allowed rover to identify AR tags from up to 6 meters away while moving 1.6 meters per second

• Designed a C++ framework to increase the number of cameras utilized for navigation• Developed an automated testing suite to determine accuracy of detection algorithms• Placed third out of 36 teams in the autonomous navigation task

• Developed a robust method of outlier filtering that used CPU threading to increase precision and reduce processing time by 68%• Implemented and benchmarked multiple Cuda algorithms for point cloud segmentation to determine the performance benefits of using GPU parallelization for obstacle identification• Wrote a C++ tool to analyze the speed and accuracy of existing point cloud processing methods and identify areas for improvement