Research profile
Clinical neuroscience and translational neurotechnology researcher.
Direct experience in conventional MEG acquisition and preprocessing, Fast-VESTAL source imaging, cerebellar fMRI, EEG analysis, and local-first research software. Work centers on fNIRS methods and reproducible analysis infrastructure; earlier work spans multimodal neuroimaging, ecological task design, source-level modeling, and software development.
At a glance
- Active work Research Lead and Software Developer, Human Neurophysiology Methods Lab; Clinical Systems Developer at Xcelsior Health.
- Core methods MEG, fMRI, EEG, fNIRS, source imaging, and experimental software.
- Direct fit areas Neuroimaging, translational neuroscience, clinical technology, and research software.
- Location Zephyrhills, Florida.
Education
Degree-only format, kept compact and easy to scan.
Publications
Published items appear first, followed by in-progress work.
Work
Ordered by target relevance, with active work first.
Develop and teach a human neurophysiology methods laboratory centered on fNIRS acquisition, reproducible workflows, and quantitative signal analysis; build a browser-based fNIRS analysis app supporting NIRx ingestion, visualization, preprocessing, filtering, and exportable protocols.
Develop and maintain clinical analytics and patient-resource web applications in Node.js, Vue 3, Tailwind, Google Apps Script, and Google Cloud for population management, care coordination, and practice operations.
Collected vitals; administered vaccines and medications; supported patient care and workflow management.
Acquired and preprocessed MEG data on an Elekta/Neuromag Vectorview system, including continuous head-position tracking, Polhemus-based MEG-MRI coregistration, MaxFilter, and temporal signal-space separation; generated and interpreted frequency-specific Fast-VESTAL source maps, including gamma-band findings; created MNI-registered MEG-derived regions of interest for fMRI connectivity analysis and downstream interpretation.
Received direct funding for a three-month multimodal neuroimaging project; Daniel E. Callan, PhD, served as co-Principal Investigator; designed and implemented an X-Plane aviation pursuit task using C plug-ins and multithreaded Java control programs; operated MEG acquisition with CiNet staff support and coordinated behavioral, MEG, EEG/MEG, and fMRI sessions.
Developed EEG/EMG biomarker workflows for mild traumatic brain injury in a simulator, including movement-locked onset detection, an EEGLAB preprocessing and simulation plugin, trial-level EEG permutation statistics, and second-order systems (SOS) filtering applications.
Field-tested radar cardiography devices for search-and-rescue applications.
Developed and tested an EEG neurofeedback interface.
Conducted psychophysiological research on vagal fluctuation in depression and brain responses to visual stimuli.
Awards and Fellowships
Formal honors and funded appointments.
Department-nominated and NSF-funded group and personalized training for teaching at the college level.
Neuroergonomic multimodal neuroimaging during an aviation pursuit task.
Teaching
Representative teaching and lab leadership across university settings.
Designed and implemented collaborative, hands-on technical laboratory curriculum in human neurophysiology methods, including fNIRS, using collected data, reproducible data workflows, and quantitative analysis.
Designed and implemented discussion and project-based curriculum on prenatal through adolescent development, integrating major theories with contemporary research across biological, cognitive, cultural, and other domains.
Designed and implemented team-based and AI-forward curriculum on contemporary biological psychology theory informed by recent advances in human and animal neuroscience and neuroimaging.
Led weekly lectures on data science topics and created interactive data science assignments in iPython notebook.
Oversaw internal professor and TA evaluations, faculty/TA cooperation, and new TA training.
Led weekly lectures on data science topics and guided undergraduate data science projects in Python and R.
Led teams of undergraduates through prototyping, user experience, and interaction design in healthcare.
Designed and implemented team-based curriculum on randomization and bootstrap approaches to introductory statistics in R, culminating in a final poster session with students presenting real data.
Led team-based experience design processes in citizen science and environmental advocacy domains.
Led weekly scrums for teams of undergraduates on web app interaction design in Node.js and MongoDB.
Led weekly lectures on data science topics and guided data science projects in Python and R.
Led weekly labs guiding undergraduates through modeling and data analysis methods in MATLAB.
Led weekly scrums for teams of undergraduates on web app interaction design in Node.js and MongoDB.
Led weekly scrums for teams of undergraduates on web app interaction design in Node.js and MongoDB.
Moderated and reviewed online materials and led discussions for a massive online open course.
Led weekly lectures reviewing nervous system anatomy, wrote and graded quizzes and exams.
Led weekly lectures discussing pharmacodynamics and kinetics of various classes of psychoactive drugs.
Led weekly lectures and assessed undergraduate teams on cognitive ethnography principles and projects.
Led weekly lectures discussing the book Cognition in The Wild and other distributed cognition topics.
Led weekly lectures on textbook parametric statistical testing, wrote and graded exams.
Led weekly lectures reviewing pharmacodynamics and kinetics of various classes of psychoactive drugs.
Held weekly office hours, hosted exam reviews, and covered a lecture.
Held weekly office hours and provided feedback during weekly problem sessions.