SYSTEM STATUS
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AI / SOFTWARE        ███████████████░   ACTIVE
AEROSPACE            ███████████░░░░░   EXPLORING
RESEARCH             ████████████░░░░   ACTIVE
CAD / 3D             █████████████░░░   ACTIVE
CURIOSITY             ████████████████   MAX
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CURRENT MISSION  → AegisLand: uncertainty-aware UAV landing safety

I'm a student at River Islands High School with a strong interest in AI systems, aerospace engineering, autonomy, CAD, simulation, and product development.

I like projects where I can go past the demo and ask harder questions: Does it work reliably? Can I measure it? What happens when the assumptions fail? That mindset has pushed me toward research-style engineering, AI evaluation, autonomous systems, and building software that people can actually use.

Right now, I'm especially interested in UAV autonomy, safety-critical AI, computational aerodynamics, flight controls, and AI-assisted engineering workflows.

Worked across production AI and product engineering for OpenStage/Seagulls, including assistant-integrated exercise search and recommendations, chat UX improvements, tracing/QA, and Core AI work around routing, memory, safety, and agent architecture.

Worked in an early-stage technical environment across AI/software research and product-oriented problem solving.

Contributed in a startup environment focused on growth, experimentation, and product execution.

Collaborated on interactive game features and technical design while working as part of a student development team.

I'm currently building toward deeper work in aerospace autonomy and computational engineering.

Autonomy        → UAV navigation, fault detection, safety supervisors
Aerodynamics    → CFD, unsteady flow, aerodynamic modeling
Controls        → sensing, flight dynamics, adaptive recovery
AI Research     → reliability, abstention, evaluation, uncertainty
Engineering     → CAD, simulation, prototyping, validation

I'm investigating whether a confidence-aware safety supervisor can reduce unsafe simulated UAV landings when visual perception becomes unreliable. The project includes a reproducible simulation, perception-stress models, an interpretable PROCEED / HOLD / ABORT supervisor, Monte Carlo experiments, confidence intervals, threshold ablations, and a preregistered Phase 1 protocol.

I'm also helping build RIAX — River Islands Aerospace, a student aerospace initiative centered on hands-on engineering, research, competitions, industry exposure, and ambitious technical projects.

cool idea
   ↓
working prototype
   ↓
repeatable test
   ↓
real data
   ↓
find what failed
   ↓
improve it
   ↺

[ BUILD ]  software products
[ TEST  ]  AI reliability
[ MODEL ]  aerospace systems
[ DESIGN]  CAD + 3D
[ LEARN ]  everything I can get my hands on

Turning curiosity into measurable engineering work.

That means building the system, testing it, documenting limitations, analyzing the results, and then improving it — whether the project is an AI benchmark, an aerospace simulation, a product, or a physical design.