Visual Feedback in Gait Retraining
Leading a human-subjects study (n=10) using instrumented treadmills. Developed a custom Python pipeline to process force-plate data and compute Peak Propulsive Force in real time.
Honors Psychology student at Portland State University specializing in human locomotion, gait biomechanics, and real-time visual biofeedback systems. Bridging rigorous data analysis with intuitive, human-centered interfaces.
Leading a human-subjects study (n=10) using instrumented treadmills. Developed a custom Python pipeline to process force-plate data and compute Peak Propulsive Force in real time.
Facilitating technical workshops on EEG hardware and OPM-MEG technology. Connecting psychology and engineering students through hands-on hardware demonstrations.
Access theoretical frameworks in Active Inference and Bioelectricity, conference field notes, and reflections from ongoing research.
GPA: 3.60. Human locomotion, gait biomechanics, and real-time visual biofeedback. Psi Chi Honor Society.
Gilman International Scholar. Studied cinema and the history of science, examining visual culture and scientific inquiry.
Prepared commercial aircraft components under tight timelines and exacting safety and engineering specifications.
Maintained a professional art practice centered on visual perception and spatial composition—now applied to intuitive biofeedback design.
Worked in the D1X semiconductor fabrication facility across complex technical workflows, cleanroom protocols, and team coordination.
Foundational study in visual theory and studio art before transitioning into neuroscience research.