Member of Technical Staff @ OpenAI

Scaling AI Infrastructure

I build scalable AI infrastructure and distributed systems. Passionate about running large-scale systems and finding elegant solutions to complex problems.

Chanzo Bryan

/// What I Do

Distributed Systems

Building scalable systems for ambitious products. Experienced in creating high-performance infrastructure that scales to billions of requests.

AI & Reinforcement Learning

Creating AI agents that master complex games. Built environments for Terra Mystica, SpeedRunners, and research into multi-agent learning systems.

Full-Stack Development

From React Native mobile apps to Rust-based game engines. Comfortable across the entire stack with a focus on performance and user experience.

/// Latest Writing

The k = 5 construction: an independent set W, five adjacent twin pairs, and the clique C. Every vertex in W connects to every twin-pair vertex, and each pair connects to three consecutive vertices of C.

Quadratically Large Regular Graphs Without Internal Partitions

Quadratic-size counterexamples to Ban and Linial's proposed linear threshold for internal partitions.

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Introducing the Prophet Ontology

Introducing the Prophet Ontology

Prophet starts from a simple idea: define your business domain once, then generate the repetitive backend scaffolding across stacks without letting contracts drift.

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/// Papers

/// Featured Projects

RDF Ontology

Prophet

Ontology-first backend scaffolding across Java, Node, and Python

A multi-stack code generation platform that compiles a single domain ontology into SQL, OpenAPI, and framework-specific integration code. Prophet reduces contract drift by generating typed actions, query APIs, persistence adapters, and migration artifacts with deterministic outputs and compatibility checks.

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Prophet
TypeScript React Native

Splice

AI-powered bill splitting mobile app

A React Native mobile app for seamless expense tracking with AI-powered receipt scanning. Built with TypeScript, Expo, and Supabase, it features real-time sync, passwordless authentication, and intelligent OCR to automatically parse receipts and split bills among groups.

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Splice
Rust Python

Terra Mystica RL

High-performance board game AI environment

A rules-complete implementation of Terra Mystica in Rust, exposed as a PettingZoo/PyTorch RL environment via PyO3. The core engine leverages Rust's performance guarantees for maximum simulation speed, while Python bindings provide seamless integration with modern RL frameworks. Includes Pygame visualization for debugging agent behavior.

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Python PyTorch

HLRL

Modular reinforcement learning library

A from-scratch RL library implementing state-of-the-art algorithms including SAC, DQN, IQN, RND, Ape-X, and R2D2. Features a flexible wrapper-based architecture that allows algorithms to be composed and mixed, with backend-agnostic core abstractions for portability. Optimized for single-machine high-performance training without sacrificing code clarity.

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Python C++

SpeedRunners RL

Deep RL agents playing SpeedRunners via direct game injection

A modular reinforcement learning system that trains agents to play SpeedRunners using direct game process injection. A C++ DLL hooks into the game to extract state and inject actions, exposing a Gymnasium-compatible environment via named pipes. Agents are trained using Rainbow IQN and RND in PyTorch, with a clean separation between game interfacing (sr-lib), environment wrapping (sr-gym), and agent training (sr-ai).

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SpeedRunners RL

Interested in working together?

Let's chat about opportunities and collaborations.

Contact Me