Yuchen Liang

Engineer specialised in electrical systems and reliability analysis, with hands-on experience in data-driven fault diagnostics, configuration management, and RAMS practices. Skilled in Python, MATLAB, and Excel for technical analysis and reporting, with a background in embedded systems deployment and vibration diagnostics in industrial environments. Strong cross-disciplinary and cross-cultural collaboration experience supporting system maintenance and engineering optimisation.

Digital Audio Processor - FPGA, 03/2024, 08/2024, Utilised Vivado’s waveform viewer and automated simulation environment to visually validate Verilog modules, enabling efficient debugging and regression testing across multiple design iterations., Deployed an audio processing pipeline on FPGA using physical controls (knob/button) and stereo outputs to demonstrate real-time responsiveness and signal integrity., Conducted real-time FFT-based anomaly detection using Python and iteratively optimised Verilog DSP logic based on spectral feedback, improving SNR by 12%. Semi-autonomous Car, 07/2021, 02/2022, Collaborated with mechanical engineering students to design a robust car body with 20% weight reduction, including sensor layout, circuit routing, and control system integration., Managed and integrated multiple sensor inputs (radar, lidar, ultrasonic sensors, and cameras) using an ARM Cortex-M4, enhancing the car's environmental perception and situational awareness., Developed control algorithms for critical functionalities, including lane-keeping assistance and adaptive cruise control, reducing 60% human intervention and improving autonomy. Tutor-Student Matching Club, 07/2020, 07/2022, Founded and led a club that successfully matched 50 tutor-student pairs within the first three months., Designed a Python-based matching algorithm to optimise the matching of tutors and students based on academic needs, skills, interests, and other criteria, reducing manual operation time by 80%., Established and managed a comprehensive MySQL database, integrating it with Python for efficient data analysis and maintenance, improving the matching process and operational efficiency.