Ata Caner Cetinkaya: Rust systems engineer, compiler engineer, AI and machine learning engineer, and open-source contributor.
Rust / C++ / 9 projects / open source merged into burn
Bring me a problem, or half an idea. What comes back is a product.
Between idea and product, the work changes hands five times: mathematician, architect, systems engineer, interface designer, and the engineer who gets it into production. All five are mine.
maths & statistics
A fuzzy idea can't be checked, priced, or trusted. I make it precise: equations, distributions, error bars. If the numbers don't hold, we find out here, not in production.
Uniswap V3 tick maths, reciprocal rank fusion, HdrHistogram percentiles, and the Navier-Stokes field behind this page.
systems architecture
Boundaries, queues, and failure modes get drawn before any code exists. What must never block, what may fall behind, what happens when it breaks: those answers are the architecture.
A lock-free price-time matching engine. An agent pipeline running a real job search.
rust & performance
Safe Rust on the hot paths; measurement across the whole system. The meter here is not a mock: it is this page profiling itself, frame by frame, right now.
Zero locks on the matching path. A sampling profiler. BLAS-backed learning maths.
interface design
Engineering that ships ugly still loses. Type, rhythm, and motion that mean something are part of the product, not paint on top. This page is part of the proof.
this site: a hand-built fluid sim, nine procedural portraits, a design system owned end to end
delivery
An idea only counts once it runs where people can reach it. The proof is below: nine projects across four domains, this site among them.
Cloudflare deployment. Tauri desktop builds. An agent storefront, live.
The line is one SVG path, drawn by your scroll. The fit is computed live; the queue sheds under pressure; the meter is profiling this page.
Everything I've built so far: 9 projects across 4 domains, one scene at a time. Have a look around.
learning systems
Two projects working with intelligence, memory and retrieval.
continual intelligence
A brain-inspired continual-learning substrate, built without backpropagation.
Learning persists across laps; nothing is ever retrained from zero.
rustbevyblas
local semantic search
Semantic search across your own image library, running entirely on your machine.
Three models argue about every image; one answer leaves the room.
rusttaurireactpython
market machinery
Two projects reading and executing the structures beneath price.
defi analytics
Local-first DeFi analytics, from Uniswap V3 mechanics to cross-DEX arbitrage.
Uniswap V3 tick maths to cross-DEX arbitrage, decoded entirely on your machine.
rusttauritypescript
matching engine
A lock-free limit-order-book matching engine, written in safe Rust.
Price-time priority with no locks anywhere on the hot path.
rusttokioratatuihdrhistogram
sharp instruments
Two projects making the invisible costs of software visible.
where time goes
A profiler that shows where programs actually spend their time, without drowning you in it.
The hot path has nowhere to hide from a sampling profiler.
c#tmodloader
learning substrate
An interactive substrate for learning hard technical material by doing it.
Structure you traverse beats prose you skim.
reacttaurimdxkatex
software that acts
Three projects where the users are programs: status, pipelines, commerce.
agent pipeline
An agent-driven pipeline that runs a job search like an engineering project.
Hundreds discovered, dozens graded, a handful tailored; volume becomes precision.
rusttokiosqliteratatui
ambient agent status
Your Mac's notch becomes a live status surface for coding agents.
Your agents' heartbeat, glanceable without ever switching context.
swiftswiftui
agent commerce
A storefront built for AI agents to buy from, not browse.
Orders placed and fulfilled by software; the storefront speaks protocol.external →
astrocloudflare workersd1
A role, a collaboration, or a product you want built. Tell me what you're thinking and I'll answer honestly.