I develop computational and engineering tools that grow out of my research on human intelligence. These projects include electrode localization, explainable AI, and pattern-identification methods for transforming complex neural data into interpretable scientific and clinical insight.
An explainable machine learning framework for linking neural dynamics to cognitive behavior while preserving feature-level scientific interpretation. The project uses interpretable models to identify neural patterns that support visual encoding and candidate markers for closed-loop cognitive neurotechnology.
A MATLAB toolkit for objectively localizing intracranial electrode contacts from CT, MRI, and FreeSurfer-derived anatomical segmentations. The workflow combines image-guided initialization, graph-based search, validation, and export for human electrophysiology research.
A wearable vibrotactile transcutaneous auricular vagus nerve stimulation system for delivering noninvasive stimulation during cognitive tasks. The project connects device engineering, physiological monitoring, and behavioral testing to evaluate how taVNS can modulate arousal and working memory.
A closed-loop rehabilitation framework that uses corticomuscular network analysis to quantify brain-muscle interaction after stroke and guide individualized transcranial magnetic stimulation. The project links electrophysiology, motor recovery, and network-level biomarkers for adaptive neuromodulation.