programmıng
My thesis project at NYU focuses on developing and evaluating a physiological musical expression that can be used as a control signal for digital audio effects.
By incorporating commercial Electroencephalography (EEG) technology, the user's level of calmness is utilized to control the parameters of digital audio effect units in real-time. The study also demonstrates how machine learning technology can be used to transform EEG data into individualized mental gestures.
Implemented in Max/MSP, this project integrates various software and hardware tools for the acquisition, transmission, calibration, and remodeling of EEG data.
Publication
In 2017, I collaborated with Marlene Mathew and Professor Agnieszka Roginska at NYU to develop BSONIQ - an EEG-based 3D audio installation - which translates brainwave data into the audio domain through 14 loudspeakers. Here’s the published work from the International Conference on Auditory Display.