Design engineer · founder · investigator
Exoskeleton dynamics. Energy-risk intelligence. AI decision systems. I build far enough to find out what is true—and what might be worth building next.
Currently selecting the next company to build.
Facts that are useful before the adjectives.
EU-wide Amazon AI competition
profitability analysis accuracy gain
incremental revenue generated
Apple Swift Student Challenge
What I have looked at seriously.
Investigated how energy companies and insurers price long-duration environmental liabilities under uncertainty. Built the data, validation, and modeling system; paused before turning the investigation into an operating product.
Inspect →The next problem: a high-stakes decision where the evidence exists but no system turns it into confident action. The work above is the evidence base, not the conclusion.
Talk →Artifacts that make the pattern visible.
Modeled and simulated an articulated lower-body mechanism in MATLAB/Simulink, then inspected its motion and system response.
A product system explored through research, interaction, and a long-form visual design artifact.
Data-driven research and high-fidelity prototyping that reduced client acquisition cost by 90% and improved engagement by 50%.
A physical engineering project: constraints, components, iteration, and the work of making a system move in the real world.
Thinking in public, now native to this site.
I started with physical systems—CAD, exoskeletons, solar cars—and moved into the software and data layers. The recurring question is the same: what does it take to turn an ambiguous problem into a system that can be tested, used, and trusted?