Chaeyeon Kim

Co-authoring a PRISMA-ScR systematic review on non-invasive brain-computer interfaces, unifying speech-decoding and auditory-modulating research. Contributing to the NeurIPS 2025 EEG Foundation Challenge by developing and benchmarking models using the Braindecode framework.

• Facilitate weekly workshops on Python, data analysis (Pandas, NumPy), and foundational machine learning concepts. • Teach supervised/unsupervised learning, model evaluation, and practical ML workflows using scikit-learn. • Mentor students through hands-on projects, including exploratory data analysis, feature engineering, and training ML classifiers. • Develop learning materials, coding templates, and interactive demos to support 100+ students across beginner and intermediate sessions. • Drive a collaborative learning environment by helping participants debug code, understand algorithms, and build portfolio-ready projects.

• Developed a non-invasive BCI system enabling gameplay using only EEG signals • Implemented live data acquisition with OpenBCI Ganglion and BrainFlow • Designed signal processing pipeline: band-pass filtering, FFT, CCA frequency detection • Built Python-based integration for real-time neural intent recognition • Created attention-based input system without eye tracking or physical controllers • Demonstrated accessibility-focused gameplay for users with mobility impairments • Collaborated with a multidisciplinary team from CS, EE, and neuroscience

Built multilingual Ameli websites in Korean, Japanese, and English. Analyzed ad performance using GA4 and Google Ads to optimize campaign effectiveness.