Notes on what I study, what research has taught me, and where I begin.
Cell Engine began with an interest in how cells respond to disease and interact with their surroundings. Simulation gives me a way to explore parts of those processes and see how they fit together.
The project is still an early prototype. Learning the biology and understanding what the model leaves out are as much a part of the work as building it.
My thesis at DFKI was my first professional research experience. Building DiversityLens meant working with a GPU cluster for the first time and tracing technical problems across a pipeline, often remotely.
That work made me more careful about how I investigate a failure: understanding how the parts connect before deciding what needs to change.
When a question stays with me, I look for a part I can work on. That usually means reading, identifying gaps in my understanding, and building something small enough to inspect.
Cell Engine follows that approach: start with a limited model, learn from its shortcomings, and use those to decide what to investigate next.