Perception · World modeling · Physical AI
I build the estimation and world-modeling systems
that let robots make sense of where they are.
Roboticist with a PhD in perception. Day to day I'm a machine-learning engineer at Voxel51, helping teams wrangle and evaluate computer-vision data with FiftyOne. Off the clock I'm building PRISM, a factor-graph world model, and Arwun, a self-balancing tracked robot it runs on.
Currently
Arwun → Isaac
Bringing a self-balancing tracked robot from Drake/LQR control onto the NVIDIA Isaac stack — Isaac ROS perception on a Jetson Orin Nano, Isaac Sim for synthetic data and sim-to-real.
PRISM world model
A GTSAM factor-graph estimation backend, a hierarchical scene graph, and an LLM-grounded policy layer — fed by accelerated perception front-ends.
FiftyOne plugins
Open-source tooling for object tracking and dataset evaluation, built on the platform I work on by day.
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