Muhammad Ali

I am a graduate Electrical Engineer with strong interest in embedded systems, IoT, and artificial intelligence. I have hands-on experience with ESP32, Arduino, PCB design, and hardware-software integration.

During my final year project, I developed an AI-driven workout assistant using MediaPipe and deep learning models for real-time posture detection and feedback. My project was awarded Best FYP in my department.

I am passionate about building smart systems that combine hardware and software to solve real-world problems. I am always eager to learn new technologies and contribute to innovative engineering projects.

Electrical Engineering graduate with practical experience in Machine Learning, Embedded Systems, CAM design, and industrial power systems. Skilled in developing real-time AI applications using Python, MediaPipe, and LSTM models, along with hands-on experience in ESP32 and Raspberry Pi-based IoT solutions.

Experienced in PCB Computer-Aided Manufacturing (CAM) and technical design tools, bridging the gap between software intelligence and hardware implementation. Completed industrial internship at a 132kV Grid Station (HESCO), gaining exposure to high-voltage systems, protection equipment, and operational maintenance.

Passionate about integrating AI, embedded systems, and smart automation to build practical, scalable engineering solutions.

I completed my Bachelor’s degree in Electrical Engineering, where I built a strong foundation in electronics, embedded systems, control systems, and signal processing. During my studies, I worked on practical lab projects involving Arduino, ESP32, PCB design, and MATLAB simulations. For my final year project, I developed an AI-based workout assistant using computer vision and deep learning, which was awarded Best FYP in my department.