- Leading the 15+ person LiDAR sub team developing an autonomous Level 4 vehicle for the SAE AutoDrive Challenge with General Motors.- Developing LiDAR-based lane detection and 3D object detection/segmentation algorithms for real-time environment perception.

- A Part of the software perception sub-team for the Queen’s Aerospace Design Team (QADT).- Developing machine learning algorithms for precision landing and autonomous flight.

- Optimizing machine learning models for accurate semantic segmentation of 3D point clouds, focusing on improving performance and reducing costs.- Developing real-time automated asset detection models to support the acquisition and inspection of image data for utility companies.- Creating and deploying an asynchronous cloud worker pipeline to significantly enhance processing speed, scalability, and efficiency in handling large-scale datasets.