High-Resolution Analytics
Using ML to artificially increase the resolution and accuracy of commodity industrial sensors—finding the signal in the thermal noise.
APPLIED RESEARCH // MATHEMATICAL LOGIC // INDUSTRIAL AI
Ghost Citadel’s research division operates at the intersection of formal methods, machine learning, and systems engineering. We translate academic rigor into deterministic, high-performance systems.
Research that never ships is a hobby. We maintain a closed-loop between original inquiry, mathematical validation, and production implementation.
We explore formal verification for industrial codebases. By applying mathematical modeling to C++ and Rust kernels, we ensure that safety-critical systems in Industry 4.0 are not just tested, but proven correct.
We build alternative ML implementations using functional principles and coordinate-free linear algebra. Our focus: models that run with extreme efficiency on ARM-based edge devices where every milliwatt counts.
Using ML to artificially increase the resolution and accuracy of commodity industrial sensors—finding the signal in the thermal noise.
Applying non-classical logic to distributed systems to minimize latency in real-time industrial collaboration tools.
Translating optical design theory into working computer-vision solutions for low-power mobile Linux devices.
We provide the testing ground for your theories. Validate mathematical models against real industrial datasets and hardware limits. Publish with confidence.
Partner with us to translate complex academic findings into working Python, Rust, or R solutions deployed against your real business constraints.