Multimodal neuroimaging
MEG source work in autism and connectivity analysis
Acquired and preprocessed MEG on an Elekta/Neuromag Vectorview system, generated Fast-VESTAL source maps, and created MEG-derived ROIs for downstream fMRI interpretation.
Multimodal neuroimaging, browser-based fNIRS analysis, and clinical systems work that has to function in real life.
Multimodal neuroimaging
Acquired and preprocessed MEG on an Elekta/Neuromag Vectorview system, generated Fast-VESTAL source maps, and created MEG-derived ROIs for downstream fMRI interpretation.
Cerebellar fMRI
Designed the X-Plane task, wrote control software, and led the full fMRI pipeline for the first-author study on cerebellum, basal ganglia, and cortex.
fNIRS methods
Open-source, cross-platform, client-side fNIRS analysis that runs in any modern browser, including offline. The app exports a transportable processing and analysis protocol: an ordered, human- and machine-readable record of preprocessing and modeling choices with parameters and provenance, reloadable to resume work and retrace decisions without data sharing.
Clinical technology
Clinical analytics and patient-resource applications developed in a stack that includes Node.js, Vue 3, Tailwind, Google Apps Script, and Google Cloud.
Publications and talks
First-author paper bridging ecological task design, cerebellar fMRI, and performance under time pressure.
Direct conventional MEG acquisition, preprocessing, and source-level interpretation supporting a multimodal analysis pipeline.
Software and methods work focused on local-first analysis, protocol portability, and reproducible processing.
Ecological task design and neuroergonomics work from the aviation pursuit study.
Measurement, analysis, software, and translation stay connected across the work.