From Raw Data to Research Results using MATLAB
Do you work with measurement data, sensor signals, experimental results, or simulation outputs?
In this practical PhD workshop, you will learn how to build clear, efficient, and reproducible data-analysis workflows in MATLAB. Starting with MATLAB variable types and data structures, you will progress from importing raw data to automating analyses and creating publication-ready figures.
You will also learn how GitLab can help you manage changes to your research code and how AI tools can support MATLAB programming, debugging, and documentation without replacing your own critical judgement.
After the first two workshop days, you will have time to apply the methods independently. A few weeks later, we will meet again for a four-hour Bring Your Own Data workshop, where you can work directly on your current PhD research with individual support.
Temptative Schedule and Tasks
- Homework pre-course: 2–3 hours of guided preparation
- Day 1 (24.02.2027): MATLAB data types, data import and GitLab
- Day 2 (25.02.2027): Time-series data, signal processing, figures, functions and classes, time and AI-supported coding
- Homework: 4 hours using your own data
- Day 3 (17.03.2027): 4-hour guided Bring Your Own Data session
You Will Learn How To
- Choose suitable MATLAB data types and structures
- Import and organise research data
- Automate repetitive processing tasks
- Work with time-series and engineering signal data
- Create publication-quality figures
- Manage MATLAB projects with GitLab
- Use AI tools responsibly for coding and debugging
- Apply the complete workflow to your own research data
No statistics or machine-learning knowledge is required.
Basic prior exposure to MATLAB or another programming language is recommended.
Leitung: Prof. Dr. Alexandra von Kameke
