Joe Shen Email & Phone Number

Vaughan, Ontario, Canada

Apart of the Autonomous Intelligent Vehicle (AIV) team developing algorithms to improve the driving behaviour and capabilities of Martinrea Alfied's autonomous vehicle platform using state of the art techniques (SLAM, computer vision, machine learning).Developed a proximity detection system by designing and training a CNN model from scratch to determine whether obstacles are too close utilizing depth images captured with a Intel RealSense D435i Camera, achieving a 97% inferencing accuracy for autonomous robotic vehicles.Currently working on integrating triton.

Toronto, Ontario, Canada

Collaborated in a Research and Technology (R&T) team for the development of proof-of-concept products within the urban rail signaling domain, utilizing Python and C++ for software development.Participated in the development of complex, real-time autonomous transportation system components, gaining experience with utilizing LiDAR and camera data.Contributed to the development and training of a YOLO model for object detection within a transportation environment, achieving an accuracy of 90% while extracting critical data for continuous improvementEnhanced software development processes by implementing efficient CI/CD pipelines utilizing Jenkins, resulting in a 20% acceleration in code deployment through semi-automated execution of unit tests.

Toronto, Ontario, Canada

Engaged with potential clients seeking jobs in the technology and educational sectors via telephone and email communication.Utilized 8x8 Voice Communications and Microsoft Excel to communicate and store client data to recruit over 30+ clients to an affiliated company.

Toronto, Ontario, Canada

Collaborated with a millwright and electrician to acquire hands-on experience in technical operations and maintenance of machinery. Aided in daily maintenance operations to achieve demanding production schedule targets increasing technician availability by 25%.Organized and maintained an inventory system composed of machine parts, filters, bearings, tools and other parts to streamline part acquisition by 20%.