Electrical Engineering Student & Embedded Systems / Robotics Researcher
I build real-time embedded control systems and robots that operate where software meets the physical world — from bare-metal firmware driving hydraulic actuators to AI-assisted perception for autonomous flight.
First Honors
KFUPM Dean's List
I'm a first-honors Electrical Engineering student at King Fahd University of Petroleum and Minerals (KFUPM), while working across embedded firmware, control systems, and applied robotics research.
I've explored and developed projects in the fields of robotics, autonomous drone systems, closed-loop systems, and machine learning. My specialty is writing bare-metal C for real-time control loops, reverse-engineering undocumented communication protocols, and closing the loop between sensors, actuators, and decision-making software. I'm currently a Research Intern at HKUST developing control firmware for a water-hydraulic soft robotic arm, alongside ongoing undergraduate research at KFUPM spanning assistive robotics.
Additionally, I am currently learning more on PCB design and electroencephalogram (EEG) for assistive robotic control through brain waves.
Currently
B.S., Electrical Engineering
King Fahd University of Petroleum and Minerals
A timeline of research positions, technical leadership roles, and hands-on engineering work.
Robotics and embedded systems projects spanning research, competition, and applied engineering. Preview images are placeholders — swap them for real screenshots any time.
Real-time bare-metal control firmware for a water-hydraulic soft robotic arm, including a reverse-engineered CAN bus protocol, a custom tendon-synchronization algorithm, and sensorless closed-loop positioning.
A dual-arm humanoid robotic hand system that mechanically translates spoken letters into American Sign Language fingerspelling in real time, pairing a Jetson Orin Nano speech-to-text pipeline with a 16-servo-per-arm, tendon-driven hand design validated in MuJoCo simulation before hardware assembly.
A hybrid drone-detection rig fusing a microphone-array acoustic classifier with a YOLOv5/TensorRT visual tracker across two NVIDIA Jetson Nanos — the acoustic side estimates bearing via direction-of-arrival, while a PID-controlled, PCA9685-driven pan-tilt camera locks onto and follows detected drones in real time.
Theeb, a 22-inch VEX U Pushback competition robot built while directing a 14-member sub-team across CAD, fabrication, and integration. Theeb went through four major hardware revisions — from an X-drive base with an S-shaped scoring channel to a lighter, color-sorting H-drive with linear scoring — backed by a PROS/LemLib software stack for sensor-fused autonomous navigation.
An autonomous drone performing AI-based human detection with 3-axis camera tracking and laser targeting, built for the Autonomous Aerial Systems Competition. Led embedded systems and electronics integration.
A Review of Acoustic Techniques for Drone Detection
IEEE Smart Cities Conference (SCC), 2025
H. Altujar et al., "A Review of Acoustic Techniques for Drone Detection," IEEE Smart Cities Conference (SCC), 2025.
View publicationLive from my GitHub profile — repositories, activity, and stats update automatically.
@HaShinobi
Robotics, embedded systems, and control software.
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B.S., Electrical Engineering
King Fahd University of Petroleum and Minerals
Dhahran, Saudi Arabia
1st Place, KFUPM Venture Tank
SAR 15,000 seed funding for Elecure
Finalist, SCI UK Bright SCIdea Challenge 2025
Youngest international team and first KFUPM freshman to qualify
Bechtel Corporation Scholarship
Awarded for academic and extracurricular excellence
3rd Place (of 10 teams), Autonomous Aerial Systems Competition, KFUPM
Led embedded and electronics integration for an autonomous drone performing AI human detection and 3-axis camera tracking with laser targeting
First Honors & Dean's List, KFUPM
Awarded for academic distinction
Reach out about research collaborations, internships, or anything embedded/robotics related.