Albert Koop

I help technical development, testing, and validation teams turn messy measurement, test, and simulation data into robust decision-making foundations.

I am a physicist with a PhD and over ten years of experience in technical and scientific environments. I have managed a magnet laboratory with multiple cryostats, supervised measurement setups, controlled hardware, commissioned equipment, and learned about data at its source: in the lab, at the test bench, in experiments, through the interplay of sensors, control systems, measurement devices, software, and people.

My scientific work has been published in Physical Review Research:

DOI:

By the end of a project, it's usually clear how the data should have been structured from the beginning. My work brings this level of order and understanding into the process earlier.

Typical projects:

- Cleaning, structuring, and documenting measurement and test data

- Consolidating CSV, Excel, log, and SQL-like data from various sources

- Standardizing units, timelines, sensor IDs, test runs, and metadata

- Visualizing outliers, drift, noise, missing values, and plausibility issues

- Creating Python/Pandas scripts for reproducible data preparation

- Reviewing and improving existing Excel or Python analyses

- Preparing data from laboratories, test benches, sensors, hardware control, or simulations for analysis and validation

Documenting technical results in an understandable way so that teams can use them further

I see data as part of a technical chain: setup, device, calibration, measurement, boundary condition, error pattern, uncertainty, evaluation, decision, next test series.

My goal: Your engineers will spend less time on data archaeology and more time on development, analysis, and decisions.