Dating apps are now one of the most common ways people meet – yet matching still relies mostly on profiles, photos, and self-reported preferences. Could sensor data do better? Recent research shows that strangers whose brains respond similarly to the same video clips are more likely to become friends later [1], and that machine learning can predict romantic attraction and rejection from brain signals recorded while people browse dating profiles [2]. This points to a question at the heart of information systems: can wearable sensor data reveal compatibility that users themselves cannot put into words?

In this thesis, you will design and run a study using our wearable EEG headphones – lightweight, everyday brain-signal sensors – to test whether brain data can predict a good romantic match. You will define the study design together with us, build the data-collection setup, run the experiment with participants, and apply signal processing and machine learning to the recordings to look for patterns of attraction and similarity between potential partners. The project sits at the intersection of wearable technology, human–computer interaction, predictive modelling, and the design of future dating platforms.

Potential research questions include (but are not limited to):

• Can brain-signal data distinguish romantic interest from disinterest?
• Are two people more compatible when their brains respond in similar ways to the same content?
• Which features and machine-learning models best predict romantic interest from wearable EEG?
• What are the privacy, ethics, and design implications of using brain data in dating systems?

You should be comfortable with (or willing to learn) basic data analysis and programming in Python or R; prior experience with EEG or sensor data is a plus but not required. Most important is curiosity about wearable technology and data-driven approaches to human behaviour.

Questions or interested? Contact michael knierim ∂does-not-exist.kit edu. To apply, please send your CV and latest transcript of records.

References

[1] Shen, Y. L., Hyon, R., Wheatley, T., Kleinbaum, A. M., Welker, C. L., & Parkinson, C. (2025). Neural similarity predicts whether strangers become friends. Nature Human Behaviour, 9(11), 2285–2298.

[2] Zazon, D., & Nissim, N. (2025). Can your brain signals reveal your romantic emotions? Computers in Biology and Medicine.