A boutique R&D studio.
Rock R&D designs and deploys AI systems that operate where the data is created: on drones, vessels, industrial machines, and remote sensors. We specialize in taking models from research papers to real hardware — optimized for latency, power, and reliability in environments where cloud connectivity is a luxury.
Rock R&D is led by its founding engineer — a defence scientist and ML systems engineer with an MEng (University of Toronto) and a BMath in Statistics & Applied Mathematics (Waterloo). His career spans the full stack of edge intelligence: research-grade perception for national defence, production AI toolchains at AMD, and real-time autonomous perception at Huawei. Engagements are deliberately limited in number.
Where the experience comes from
Each entry is attributed to its employer. This work belongs to those organizations — it is presented as résumé fact, not as Rock R&D project work.
Defence Scientist
AI research for maritime acoustic surveillance: real-time classification, bearing estimation, self-supervised pretraining for sonar (45% representation-quality gain over random init). EOIR detection/tracking for unmanned surface vehicles.
Software Engineer
Shipped 3+ CV models into the commercialized RyzenAI SDK; C++/Python APIs. >50% latency reduction and +20% accuracy on next-gen AI devices.
ML Research Engineer
Custom DL operators under hardware constraints (up to 500% efficiency gains); BEV/perception model optimization to real-time (−60% latency); edge AI platform in Python/ROS.
Graduate Researcher
Infrastructure renewal-planning framework (Markov processes, Monte Carlo) minimizing lifecycle maintenance cost.
ML Research & AI Developer
Bioinformatics deep-learning review; deployed license-plate recognition into a live surveillance pipeline.
Have a sensor, a site, or a fleet that should be smarter?
We take on a limited number of engagements per quarter. If your problem involves edge constraints, unusual sensors, or no labeled data — that's our specialty.