Resume

Key Achievements

• Cut landing gear optimization times by 35% for pre-bid designs by deriving equations for computing gradient vectors and Jacobian matrices with vector calculus and implemented them as sparse matrices/tensors in OpenMDAO
• Reduced multi-lug landing gear joint margins of safety computation times by 90% by designing a Python class inheriting from OpenMDAO utilizing multi-joint force and moment equations and solving for the maximum and minimum stresses
• Minimized landing gear mesh generation computation times by 60% to 95% by expressing conventional loops and statements as vectorized NumPy operations leveraging the computational efficiency of NumPy
• Reduced pre-bid labour costs by automating the generation of Margins of Safety reports using OpenPYXL and Python in addition to automating the generation of landing gear cross sectional geometry plots with MatPlotLib for pre-bid reports
• Ensured codebase integrity with unit tests with PyTest for verifying stress class method outputs and error handling

Key Achievements

• Developed an indoor drone localization system for GNSS-denied environments at 15% cost of traditional systems utilizing a camera-vision based approach implemented with ROS on an Nvidia Jetson Nano computer in tandem with a Pixhawk flight controller achieving an accuracy of 30 cm on a multi-rotor drone indoors
• Localized the drone globally by determining the positions of ArUco markers with OpenCV relative to the drone and performed coordinate system transformations to determine the global position of the drone for autonomous flight

GPA: 4.11/4.33 (Ranked top 5)

First place in the senior division for developing a pill dispenser to assist the elderly.

Recognized for outstanding contributions to unmanned aerial systems and a vision for the future of unmanned aerial systems.

First place in the senior division for developing a skate-board locker rental system encouraging physical activity.

First place in Canada's premier drone competition for the development of a UAV system for disposal of potentially hazardous packages.

First place in Canada's premier drone competition for the development of a medical delivery drone system for remote regions.

Recognized for outstanding achievement in Grade 11 University Physics.