I learned to build systems first as mechanisms and music: preserve the object, respect the constraint, make the interface playable, then test against reality.
At sixteen I started designing physical tools for medical-device manufacturing at Applied Medical: pneumatic robotic tools, manipulators, fixtures, EOAT, CAD, prototypes, qualification, and shop-floor debugging. Complexity had to compress into reliability because the work sat next to production.
Before that, FIRST Robotics taught design under time pressure. FRC 3476 "Code Orange" won a World Championship, IRI Championship, and Industrial Design Award while I co-led mechanical design. The lesson that stayed: immature design tries to control too much, then compromises the parts that really do have to be controlled.
Through those years I played competitive piano, taught, improvised, and performed. Music gave me the other half of the method: structure first, expression inside structure, revision by attentive listening.
I eventually accepted that modeling intuition, not merely using it, was the problem I kept circling. UCSD became the formal phase: Cognitive Science with a Machine Learning & Neural Computation specialization, reinforcement learning with Mattar, neural data science with Voytek, and design-research work with Hyundai and Ford through The Design Lab.
At RAM Labs I worked across tactical cybersecurity, vulnerability repair, distributed edge inference, and proposal-driven research. I designed graph and transformer-family architectures, led a $250k SBIR as PI, co-invented a deep-learning bug-fixing patent, built pySABRE for blockchain consensus simulation, and represented the company at Google for DARPA FACT.
At a Drone Services Startup and through consulting, I shipped production systems end-to-end under aggressive cost and time constraints: architecture, implementation, deployment, and operations. The useful pattern is boring in the best way: stabilize the representation, expose uncertainty, and leave the human operator with a handle.
The through-line across thirteen years is not a genre. It is a way of decomposing ambiguous work into stable objects, typed relations, hard validators, and learned residuals. Frisbee intake. Piano motive. Pneumatic fixture. T-UEBA pipeline. CAD object graph. Same instinct under different consequences.
In person, another part of the work becomes more visible. I listen for what a team is actually trying to make, notice where the idea loses force, and help people choose a sharper direction without taking the work away from them. The result is often less confusion, a higher bar, and a much clearer next experiment. I think of this as technical and product judgment, but it comes as much from music and making things with people as it does from engineering.
The strange parts should earn their place by making the practical parts clearer.