Robotics · Embodied AI · VLA

Hello, I'm Chase.

I build the bridge between physical robots and intelligent foundation models.

Robotics engineer working across perception, motion planning, trajectory optimization, control, calibration, simulation, and large-scale robot learning infrastructure.

Explore my work Read the blog GitHub ↗

Open to collaboration

About

Full-stack robotics, from hardware to foundation models.

My background spans mechanical engineering, robotics, and artificial intelligence. I have contributed to self-built simulation engines and robot motion control libraries, with hands-on experience from hardware design and system integration to algorithms and software infrastructure.

Currently, I focus on VLA data processing, large-scale robot dataset construction, and foundation model pre-training for embodied AI. My goal is to build robots that can perceive, understand, learn, and interact with the real world.

Selected open source

Building in the open.

Projects and infrastructure I actively contribute to.

An end-to-end, GPU-accelerated platform for general-purpose embodied AI. Unifying high-performance simulation, generative data pipelines, modular model architectures, and training workflows for faster experimentation, deployment, and Sim2Real transfer.

Embodied AI
GPU Simulation
Robot Learning
Sim2Real

GitHub Documentation

A focused C++17 robotics library with Python bindings. Providing robot models, kinematics, trajectory generation, sampling-based planning, collision queries, and pose retargeting in one modular toolkit.

Robotics
Motion Planning
Kinematics
C++ / Python

GitHub

A lightweight Python framework for robot and peripheral orchestration. Coordinating robot trajectories and asynchronous peripheral tasks with motion synchronization, unified request lifecycles, and device health monitoring.