Built the pipeline behind a commercial eye tracker
Data scientist for the company's move into brain research: the analysis pipeline, plus experimental protocols for detecting neurodevelopmental and neurodegenerative markers.
Question. What does it take to turn a commercial eye tracker into an instrument that produces research-grade data — and into a tool for detecting markers of neurological disorders?
What I did. As a data scientist at Purple Gaze, I built the company’s data analysis pipeline for eye-tracking data, improving researchers’ ability to extract structured insight from complex eye-movement patterns. I also led the conceptualization and design of new experimental protocols aimed at detecting markers of neurodevelopmental and neurodegenerative disorders, and was responsible for aligning the company’s software and hardware capabilities with that research mission.
Method. Eye-movement processing and feature extraction; reproducible analysis pipelines; experimental design for clinical and research applications. The protocols and pipeline are available on the Purple Gaze GitHub repository.
Why it is here. This is the clearest example of the translation problem in my work: a measurement device is not a scientific instrument until someone specifies what it should measure, builds the processing that makes the signal usable, and designs the protocols that turn it into evidence. That gap — between a sensor and a result you can trust — is the same one that runs through the rest of my research.
Role. Neuro Data Scientist, December 2021 – March 2023.