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Hakimmie Bin Zainal
Electrical & Electronics Engineering Graduate
Focused on Industrial Systems, Robotics, and Applied AI
Hakimmie Bin Zainal
Electrical & Electronics Engineering Graduate
Focused on Industrial Systems, Robotics, and Applied AI
I’m Hakimmie Bin Zainal, a Bachelor Degree of Electrical & Electronics Engineering graduate from Universiti Malaysia Sabah in 2025, with hands-on experience in industrial electrical maintenance, motor testing, and engineering projects involving robotics and computer vision.
Currently undergoing the PROTÉGÉ–GEES programme at PETRONAS Chemicals Methanol Sdn. Bhd., where I work with HV systems, motors, and safety-driven maintenance practices.
Publication
Publication
H. Zainal, M. K. Tan, C. F. Liau, S. S. Yang, M. Yang and K. T. K. Teo, "Impact of Image Quality on YOLOv7-based Face Detection Accuracy," 2025 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET), Kota Kinabalu, Malaysia, 2025, pp. 573-578, doi: 10.1109/IICAIET67254.2025.11265664.
University's Project
University's Project
YOLOv7-Based Face Tracking Robot
October 2024 – July 2025
YOLOv7-Based Face Tracking Robot
October 2024 – July 2025
Built a YOLOv7-based robot capable of real-time face tracking at ~40 FPS on Raspberry Pi 4
Trained YOLOv7 on a custom face dataset with 150 images annotated using LabelImg for improved accuracy
Fine-tuned detection thresholds to optimize YOLOv7 performance under real-world tracking conditions
Integrated trained model into a four-wheeled robot for dynamic face tracking in indoor environments
Self-Balancing Two-Wheeled Robot
October 2024 – February 2025
Self-Balancing Two-Wheeled Robot
October 2024 – February 2025
Designed circuit and control algorithm on ESP32 using Arduino IDE, integrating MPU6050 for stability control
Achieved 95% stability using PID tuning, reducing recovery time by 30% compared to previous prototypes
Designed, assembled, and soldered a compact perfboard layout, resulting in a 25% reduction in hardware footprint
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