Research
Personalized Neuromodulation
Building an evidence base for brain stimulation that adapts to the individual, from real-time EEG decoding to clinical rTMS across four conditions.
Research Focus
Brain stimulation, tailored to the person
Cody’s work is built on one conviction: neuromodulation should be personalized. Instead of a fixed, one-size-fits-all protocol, his research pushes toward stimulation that is informed by each brain’s own activity, combining clinical trials of rTMS with the engineering needed to make stimulation adaptive and closed-loop.
Graduate Thesis
A real-time EEG brain-state decoder
At Johns Hopkins University, Cody developed a real-time EEG-based brain-state decoder and adaptive controller for closed-loop neuromodulation, work carried out under the mentorship of renowned biomedical engineer Dr. Nitish Thakor.
Conventional stimulation runs open-loop: it delivers the same pattern regardless of what the brain is doing. A closed-loop system instead reads brain activity as it happens, decodes the current state, and adjusts stimulation on the fly, a step toward neuromodulation that responds to the individual brain in real time rather than following a fixed script.
Clinical Research
rTMS across four frontiers
Repetitive transcranial magnetic stimulation (rTMS) uses magnetic pulses to non-invasively modulate specific brain circuits. Cody’s clinical research explores it as a personalized treatment across four conditions, with multiple manuscripts currently under review.
rTMS protocols targeting the neural circuits implicated in mood regulation, as a personalized option for major depressive disorder, a particularly important avenue for patients who have not responded to medication.
Research Settings
Where the work happens
Johns Hopkins University
Graduate research on closed-loop neuromodulation and real-time EEG decoding, mentored by Dr. Nitish Thakor.
UArizona Brain Imaging & TMS Lab
Clinical rTMS research and multimodal neuroimaging at the Tucson College of Medicine.
JABSOM, Honolulu
Research at the John A. Burns School of Medicine, bridging engineering and hands-on patient care.
Methods & Skills
Fluent across the neuro-data stack
Cody’s methods span the full pipeline, from acquiring and cleaning EEG, to decoding brain states with machine learning, to integrating multiple imaging modalities into a single picture of the brain.
Multiple manuscripts currently under review.