I Bridge Research and Production at the Hardware-Software Boundary
If your team found a paper they can't implement, or your systems can't keep up with AI advances — I sit at that intersection.
What I Do
I take academic research — papers from arXiv, conference proceedings, obscure journals — and implement it as production-grade systems code. C++ kernel patches, FPGA bitstreams, computer vision pipelines, cryptographic protocols. Not reports. Working software.
Most teams have a gap: their ML researchers can't write production C++, and their systems engineers don't track academic literature. I'm the person who does both — scanning thousands of papers weekly and shipping patches that shave milliseconds, megabytes, or hallucinations out of production systems.
Extract → Validate → Surface
Every engagement follows the same pattern — whether it's a research-to-implementation sprint or an evidence pipeline
Extract
Scan the research landscape, instrument the production system, or ingest the raw data. Find the signal — whether it's a niche paper with zero citations or a bottleneck buried in a profiling trace.
Validate
Prove the fix works before deployment. Benchmark against real workloads, verify cryptographic integrity, test against adversarial inputs. No hand-waving — reproducible evidence.
Surface
Ship the implementation. A clean PR against your codebase, an auditable evidence trail, or a deployed pipeline. The deliverable is working software, not a consulting deck.
Have a Bottleneck?
If your team is stuck at the intersection of research and production — let's talk. Remote consulting, fixed-price engagements, 1–3 month sprints.
Get in Touch