Performance is a function of what you control. So I control all of it.

I build bare-metal, high-performance systems — the fast, low-level code under hard problems. CUDA, Rust and C/C++ where latency and control decide the outcome; Python where it pays. Solo, end to end, on my own hardware (RTX 5060 Ti / Blackwell sm_120, Arch Linux) — with benchmarks anyone can re-run.

I'm a performance/systems engineer first. The domains below — quantum, neuroscience, materials, energy — are just where I point the same skill. The through-line: physics computes by minimizing energy; I write the systems that exploit it, at the metal.

Stack: CUDA (hand-written kernels, sm_120 roofline) · Rust (control loops, systems) · C / C++17 (compile-time guarantees) · Python (ML, glue, analysis). No cloud, by choice.

A multi-physics / quantum-biology simulation engine. The physics is the hard problem; the point is the engine underneath: hand-written CUDA (sm_120) with an honest, kernel-only roofline — 3×→154× vs JAX-CPU, end-to-end break-even stated, not hidden — plus tensor-network solvers for many-body systems. Start here if you want to know whether I can write fast kernels and back the numbers.

BLACKWALL · ICEPICK · FLATLINE — I reverse-engineer the silicon I run on. A three-part Blackwell (sm_120) teardown, hand-written CUDA: the compute roofline (BLACKWALL), the microarchitecture beneath it — instruction latencies, caches, the SASS the compiler actually emits (ICEPICK), and the energy/thermal wall (FLATLINE). The metal, measured directly — compute · communication · energy.

AETHER — I implement hard physics correctly. Computational-materials lab: electronic structure, the full topological set (SSH, Haldane, Kane–Mele), metamaterials, GPU-accelerated solvers, inverse design. ~90 tests; every claim checked against a closed form. Correctness isn't optional.

KHAOS — I build real-time systems where safety is enforced, not hoped for. Closed-loop BCI kernel: a CUDA DSP hot-path, stimulation limits guaranteed by the C++ compiler (static_assert), three independent safety layers, post-quantum audit ledger. Sub-100 µs is the design target — marked unverified until benchmarked end-to-end.

HELIOS — I build control loops that can't go down. 24/7 predictive DC-microgrid controller. Rust MPPT loop (100 ms tick), CNN-LSTM forecasting, post-quantum trust anchors. Where the lights actually have to stay on.

DRIFT — I see the structure under the problem. Optimization, self-assembly and neural memory (Hopfield) read as ground states of one Ising Hamiltonian — the unification thesis, made measurable and benchmarked against the Landauer floor of computation.

Blaze — I compress massive scientific & quantum data on the GPU. Tensor-Train / MPS compression, GPU SVD, MPS↔circuit bridge. The specialist tool the rest of the ecosystem leans on.

More in the repos — same spine, other proving grounds. Everything is mine, on my own hardware, reproducible.