I'm a graduate student in the Department of Computer Science and Engineering at UCSD, researching generalizable manipulation policies for all embodiments (humanoids, static manipulators, etc.) in Xiaolong Wang's Lab.
I was previously a Software Engineer for the Powertrain Data and Automation Team at Lucid Motors in the San Francisco Bay Area. I completed a B.S. in Mechanical Engineering with a concentration in Computer Science at UCLA, where I worked on surgical robotics research in the Mechatronics and Controls Lab advised by Dr. Matthew Gerber and Prof. Tsu-Chin Tsao.
I'm passionate about robot learning 🤖, reading 📘, climbing 🧗, and surfing 🏄♂️!
If you love reading/learning like me, but often find yourself losing track of articles, podcasts, etc. across different platforms, check out my website the someday times!
The best way to reach me is via X (Twitter) or email.
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Research/Projects
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Gentle Robotics - Teleoperation Platform for Humanoids
Building a robust teleoperation platform for humanoid robots, enabling intuitive and precise remote control for research and real-world applications.
Check it out on @gentlerobots on 𝕏 for updates!
Teleoperating the G1 to pick up a pot (in headset + outside views)
Outdoor teleoperation of the G1
Metaquest G1 hand teleoperation
CrowdBot - Crowdsourcing Quality Robot Foundational Model Training Data
Initial release complete! My friend Philip Fung and I working on a project to standardize training data for hackers, engineers, and researchers and make it as low-cost as possible. I have designed standardized hardware (camera locations, lighting, etc.) merged into the officialSO-100 arm repo for solo and bimanual manipulation.
Towel folding demo!
Primary (Color) Care Bot
As a color-blind person I often struggle to differeniate small brightly colored cubes, so this is pretty much what I need most in my life. Utilizes ACT and trained on 150 teleoperation examples. All videos at 2x speed.
CURRENT GOAL: Allow robot to clean up several cubes all at the same time (instead of one by one)!
Banana-Grama-Bot
Applied custom letter tile image processing (overlay shown in videos below) to transformer robot learning model (ACT) in fork of cmcgartoll/LeRobot Takes a letter sequence input, and the robot learns how to grasp a letter and which location to place it! All videos at 2x speed.
Spelling the word NAP!
Letter N -> Location 1
Letter A -> Location 2
Letter P -> Location 3
Even robust to regrabbing if first grab fails!
Top down videos are shown with the image overlay used for training and fed through the model during inference.
Checkout my model:
CURRENT GOAL: Allow the robot to pick any letter out of a sea of letters. Current work is on expanding this to handle multiple letters and different letter orientations!
Low-Cost Robot Learning
End-to-end trained robotics models built from HuggingFace open-source project LeRobot. All videos at 2x speed.
3 examples of successful inference from just 50 examples! Checkout my model: