Ryan Partridge — Software Engineer · RL Researcher

Programming the Future

By exploring smaller, more powerful AI systems that are explainable, transparent, and an asset to humanity - not a replacement.

See what I'm building
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01 — Mission

What I'm building

Four properties, one intelligent system. Every project builds towards it.

Requirement 01

Lightweight

Small in scale and powerful by design.

Requirement 02

Adaptive

Trained in one domain and still usable in another.

Requirement 03

Memory

Persistent in memory and continuous in learning.

Requirement 04

Transparent

Clear in reasoning and explainable by design.

02 — Projects

What I'm building

A growing set of complementary open-source tools that stack toward one mission-driving framework.

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Velora
v0.3.0 — Liquid RL research framework
Updating

A Flax-based Liquid RL research framework for small and powerful AI models. Combines Closed-form Continuous-time (CfC) Liquid Neural Networks with DiscoRL meta-learning and custom techniques to build adaptive AI agents.

Python JAX Reinforcement Learning AI Framework Research
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Envrax
v0.1.4 — JAX-native RL environment builder
Live

A lightweight, Gymnasium-style API standard for JAX-native RL environments. Includes base classes, spaces, wrappers, and a shared registry. GPU/TPU-native, vmap-friendly, and fully jit-compilable.

Python JAX Reinforcement Learning Environments API Standard
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Mujorax
v0.1.0 — JAX-native MuJoCo environments
In Development

A JAX-native MuJoCo environment suite for Envrax. Registers 25+ Playground environments (DM Control, locomotion, and manipulation) into Envrax's registry. Uses MJX-backed physics suitable for continuous control tasks.

Python JAX Reinforcement Learning Environments MuJoCo
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Velora Analytics
v0.1.0 — Analytics for liquid agents
Coming Soon

An analytics platform for Velora agents.

Analytics Explainability Dashboard
03 — Explore

Explore my work

Check out my project code on GitHub, or the research and thinking behind them on Medium.