I’m Ali Abosaad, a Toronto-based robotics and mechatronics engineer working across mechanical design, perception, state estimation, control, machine learning, embedded systems, and real-world robotic platforms.
Each project highlights the engineering decisions, system architecture, experimental validation, and real-world impact—not just the final outcome.
A lightweight navigation and state-estimation pipeline for quadrotors operating without GPS or external localization during runtime.
Perception and system-integration work for York University’s autonomous racing team.
View case study →A complete autonomous mobile robot capable of detecting, approaching, aiming at, and suppressing fires.
View case study →A collection of mechanical and mechatronic systems developed through CAD modeling, mechanism design, electromechanical integration, prototyping, and engineering visualization.
View case study →Design, modeling, and real-time control of a 2-DOF twin-rotor electromechanical system using two brushless motors, optical encoder feedback, and PID control to stabilize the platform in pitch and yaw.
View case study →Research presented for both fast scanning and deeper technical exploration.
A compact CNN prunes unreliable visual features, while adaptive thresholding, Lucas–Kanade optical flow, IMU/range compensation and EKF fusion enable efficient GPS-free quadrotor state estimation.
Developed sensing, state-estimation, simulation, actuator-modeling, control-integration and real-time robotic validation workflows for autonomous platforms.
Worked on onboard quadrotor navigation, mechatronic prototypes, sensor integration, dynamic modeling, HIL testing, actuator mechanisms and real-time control.
Designed and tested electromechanical systems and assemblies for industrial automation and mechanical product development.
Supported vehicle-dynamics and steering/braking actuator-response modeling for control-system testing and validation.
Delivered practical instruction in machine learning, deep learning, computer vision and reinforcement learning, while mentoring end-to-end student projects.
Capabilities grouped around engineering work.
Computer vision, optical flow, visual-inertial methods, feature tracking, perception systems, and sensor calibration.
Kalman filtering, sensor fusion, PID, MIMO control, stability analysis, dynamic modeling, and HIL validation.
Python, C++, ROS / ROS 2, OpenCV, PyTorch, TensorFlow, MATLAB/Simulink, and Git.
SolidWorks, ANSYS, mechanical design, mechanical assemblies, electric actuation, embedded integration, rapid prototyping, and system testing.