A selection of my work in software and acoustical engineering.
Project: Refactor and migration of internal software for vehicle engine calibration
Description: Ensured compatibility and maintainibility accross different GUI platforms in Matlab 2016 and 2022 versions to ensure proper refactor and migration of internal software.
Key features and metrics: created onboarding documentation for developers and users, used Git workflows.
Project: Automated Monitoring System
Description: Designed and implemented a system to collect and analyse embedded systems data, reducing manual tasks by over 72 minutes daily.
Technologies: Python, bash, SQL
Key features and metrics: Reduced manual tasks of the engineering team by 72 minutes daily, built a JSON parser.
Project: Reliability Toolkit
Description: Researched, developed, and deployed a toolkit for generating reliability, availability, and maintainability metrics to comply with CENELEC standards.
Technologies: Python, CSS, HTML
Key features and metrics: Automatically built report with comprehensive graphics, 100% test coverage using pytest.
Project: Vibration-Based Train Speed Estimation using Machine Learning
Description: Used machine learning to estimate train velocity using vibration signals captured by accelerometers.
Key features and metrics: Achieved a 45% reduction in Mean Absolute Error (MAE) compared to the baseline, from 10.85 km/h to 5.93 km/h, and engineered 42 features from raw vibration data.