Pauline Schomaker

Hi there! I'm Pauline, and I recently completed my MSc in Computational Cognitive Science, where I focused on Brain-Computer Interfaces (BCI) and EEG research. I have hands-on experience working with EEG systems and analyzing neural data using tools like Matlab, Python, and R. Beyond the technical side, I’ve built strong communication and project management skills through leadership roles in various projects. I’m really passionate about pushing the boundaries of BCI technology and exploring new ways to improve how humans interact with computers.

On this page, you'll find details about the projects I worked on during my Master's program. I’m excited to continue building on these as I move forward in my career.

 

Latest Project: Thesis

For my Final Research Project (Thesis), I did an internship at g.tec medical engineering (Austria), a company that specializes in high-performance brain-computer interfaces and neurotechnologies. I had the opportunity to work with their new high-density EEG system, g.Pangolin, to map the neurological activity associated with grasping movements. This experience was a huge period of growth for me, and I’m really glad I took on the challenge. The results of the project were presented at both the g.tec BCI Springschool and the Graz BCI Conference '24.

Image: Illustration of our grasping research setup.

Prototyping

As part of the Applied Cognitive Engineering course, we designed a prototype for a window heads-up display for a ship's bridge. The goal of this project was to assist sailors with navigation and help prevent collisions, particularly with bridges in waterways. Our interactive display could be customized to meet the shipper's needs and was controllable via touch screen or mouse. To develop this design, we conducted thorough research, including interviews with industry experts and visits to a maritime school, where we had the opportunity to pilot a ship simulator.

Image: The design we projected on the company's prototype window.

EEG Research Project

In my first year of the Master's program, I worked on EEG experiments and analyzed the data we collected. It was my first time working with real EEG data, and I learned a lot throughout the process. After the project wrapped up, I stayed on as an EEG research assistant to help collect more data. My analysis focused on error-related negativity (ERN), looking at how the brain reacts to errors in different conditions, which you can see reflected in the topographies on the right.

Modelling Liar's Dice

For the Cognitive Modelling Complex Behaviour course, we developed AI opponents for the game Liar's Dice. We built it in Swift, so the final product was fully playable on iOS devices. One of the toughest challenges was modeling the bluffing aspect of the game, but with reinforcement learning, we managed to integrate it into the cognitive model. In the end, we had a working game — and more often than not, the AI would actually beat us!

Get in touch