Graduate researcher in Electrical & Computer Engineering. Former U.S. Air Force Computer & Satellite Communications Specialist. Building at the intersection of biomedical signals, RF electronics, embedded systems, and astrophotography.
I'm a graduate researcher in Electrical & Computer Engineering working at the intersection of biomedical signals and hardware — surface electromyography, RF electronics, autonomous robotics and the embedded systems that tie them together.
Before graduate school I served as a U.S. Air Force Computer & Satellite Communications Specialist, and spent 15+ years in software engineering — full-stack web, test automation, and analytics. That systems-thinking background still shapes how I build.
Surface EMG acquisition & biotechnology. sEMG biofeedback, embedded ML pipelines, RF instrumentation.
End-user application delivery with React, Vue & Node.js — external APIs, Firestore/Firebase data, and UI, in an agile scrum team.
Summer research intern in the Intelligent Computing and Embedded Systems (ICE) Lab at San Francisco State University — a hub for hands-on student research focused on human-machine interfaces, neural-controlled artificial limbs, and embedded systems, directed by Dr. Xiaorong Zhang in the School of Engineering.
Contributed to the nEXO neutrinoless double-beta decay experiment; prior work at SLAC.
Front-end lead on volunteer delivery teams for a tech-education non-profit; prototyping to post-delivery support, plus technology mentoring.
Electrical & Computer Engineering — mechatronics, embedded systems, signal processing.
Combat Computer Communications Specialist & Electronics Technician — comms systems deployment and management.
PLL-synthesized broadcast FM transmitter repair and RF analysis, with an interactive wire schematic, channel calculator, and full repair report.
View ProjectAutonomous laser entertainment robot. Servo-driven pan/tilt with motion-pattern programming.
Mobile autonomous platform with sensor fusion for obstacle avoidance and path navigation.
Surface EMG signal acquisition with Xmega A1U Xpro MCU driving smart shiatsu timing via ML pipeline.
Asset tracking app for home residents. Photograph items with your phone or tablet, organize by room, and export a full inventory report — before disaster strikes.
View AppExplore potential employment locations by activity and job type. A personal job-trip diary for career dreamers.
View on GitHubResearch intern contributing to the nEXO neutrinoless double-beta decay experiment. Prior work at SLAC National Accelerator Laboratory.
A self-paced course that runs from "what even is an ODE" to solving systems with eigenvalues and Laplace transforms — so day one of the real class feels like review. Each lesson pairs plain-language explanations with fully worked examples and practice problems that reveal solutions on demand, capped by three auto-graded checkpoint quizzes. Progress saves automatically in your browser.
A six-week self-study program covering everything from vectors and matrix operations to eigenvalues and linear transformations — so day one of the real class feels like review. Each of the 24 lessons pairs concept explanations and worked examples with four practice problems that reveal solutions on demand, capped by six auto-graded weekly quizzes plus a formula Reference Sheet. Progress saves automatically in your browser.
A web-based study application for ENGG 245 / ENGR 270 Materials Science covering PS 5–11. Each problem set has four study modes: concept reviews, multiple-choice quizzes with instant scoring and explanations, vocabulary flashcards, and a full formula & Q&A reference sheet. No installation or download required — runs entirely in your browser.
Active member of the IEEE Computer Society. Engaging with the global engineering community on embedded systems, networking, and emerging technologies.
IEEE Collabratec ProfileOpen source software offers low-cost licensing and significantly lower development, hosting, and maintenance costs compared to commercial CMS or Microsoft-stack alternatives.
Read MoreEuropean researchers using photonics to develop a 1.6 Tb/s internet backbone that cuts power consumption by 50% per Gb/s — a major step toward sustainable networking.
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