I love coding!

Methodical Attention to detail Computer-savvy

And I don’t mean just writing code. It’s rather the development of algorithms that I find fascinating.

See, performing repetitive tasks is immensely boring to me. Rather, I’d spend even longer automating a task than doing it manually.

The programming language doesn’t really matter. Sure, I ‘speak’ a few including Python, C/C++, Matlab, a bit of JavaScript/html/CSS, etc. but once you understand the principles, learning another language is simply a matter of time and practice.

This happened to me time after time, during every major project I worked on during my academic course. First, I learned Python to implement an algorithm that I designed for simultaneous localization and mapping (SLAM) of a robot moving in an unknown environment towards a linguistically defined target. Next, I learned scripting FreeCAD for my MSc thesis project, where I designed an MRI-compatible pneumatic actuator, sensor and valve system. And the story repeated itself during my PhD work, where I learned scripting ImageJ/Fiji quite extensively in a Python wrapper around Java called Jython.

When writing a piece of code, I enjoy making sure that every little detail is taken care of. From code modularity and maintainability, to performance and optimality. Especially when it comes to demanding projects that may pose constraints on computer resources (e.g. computational power and/or memory consumption), writing code that makes the most out of the available hardware is key. This could mean either designing the code to be in harmony with the hardware architecture, or parallelizing the algorithm to perform certain tasks faster.