Thesis: Fault-Tolerant Control of Autonomous Systems (QCar2 Camera + LiDAR)
Coursework: Advanced Robotics, Computer Vision, Deep Learning, Machine Learning, Foundations of AI
Bridging the gap between
Who I Am
I'm a PhD candidate in Electrical Engineering at Wright State University (GPA 4.0), specialising in Control Systems & Robotics. My research focuses on fault-tolerant control of autonomous systems — building architectures that stay safe even when sensors fail.
Beyond theory, I commission real robot cells from scratch: mechanical setup, wiring, calibration, and software. I've brought up Franka Emika FR3 and Universal Robots UR5 platforms, integrated Intel RealSense depth cameras for pick-and-place, built conveyor vision-sorting systems, and designed PLC/HMI programs on Allen-Bradley hardware.
Open to: Robotics Engineer · Autonomous Systems · Control Engineering · Perception / CV · R&D — relocation welcome.
Technical Stack
What I've Built
Developing and validating fault-tolerant vehicle control architecture with automatic sensor-degradation detection on the Quanser QCar2 platform. Designed safe fallback modes ensuring stable autonomous operation under partial sensor loss. Optimising lane-keeping performance across varied real-world environments.
Designed LQR controllers for quadrotor UAV attitude, altitude, and position control. Linearised 12-state nonlinear equations of motion numerically. Implemented EKF sensor fusion eliminating ~30° gyro drift.
Full robot cell commissioning from scratch: mechanical setup, wiring, software, and camera-robot calibration. 6-DOF pose estimation from point clouds, grasp programming, repeatable physical validation.
Closed-loop physical system: real-time depth-camera detection, object classification, and automated diverter actuation on a running conveyor. Fully wired and validated on hardware.
Self-driving lane detection system for autonomous navigation on the QCar platform using classical and learned computer vision with OpenCV.
Modular Python simulation for autonomous vehicle control implementing Kinematic Bicycle Models and PID trajectory tracking for path planning research.
Semantic codebase visualisation and discovery engine generating interactive software architecture maps for navigating large codebases.
Designed and fabricated a 33 µH inductor and buck-boost converter with full electrical calculations. Validated MPPT algorithm in MATLAB. Results published at USC Conference 2023.
Research Output
Continuing Education
Career Journey
Get In Touch
I'm actively seeking full-time roles in Robotics, Autonomous Systems, Control Engineering, and Perception. Open to relocation and eligible to work in the US under F-1 visa (OPT/STEM OPT), with openness to sponsorship.