Projects


A selection of my work in software and acoustical engineering.

Project 1: 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 2: 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 3: Vibration-Based Train Speed Estimation using Machine Learning

  • Description: Used machine learning to estimate train velocity using vibration signals captured by accelerometers.
  • Technologies: Scikit-learn, Scipy, Librosa, Pandas, Numpy
  • 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.