Mingxi Jia
140 posts
@MingxiJiaa
PhD student @BrownCSDept | Before at @Northeastern. I work on building robots that are helpful and lovable.
This is joint first-author work with Zilai Zeng @zilaizeng, collaborating with Mingxi Jia @mingxijiaa, advised by Yilun Du @du_yilun and Chen Sun @jesu9. Site: diffusion-supervision.github.io/silvr arXiv: arxiv.org/abs/2506.06658 Come visit us at #ICLR2026 on April 24th 10:30am, Poster #1907!
The holy grail of robotics is to be able to perform previously-unseen, out-of-distribution manipulation tasks “zero shot” in a new environment. NovaFlow proposes an approach which (1) generates a video, (2) computes predicted flow — how points move through the scene — and (3) uses this flow as an objective to generate a motion. Using this procedure, NovaFlow generates motions in unseen scenes, for unseen tasks, and can transfer across embodiments. To learn more, we are joined by @Hongyu_Lii and @jiahuifu_carol from RAI. Watch Episode #63 of RoboPapers with @chris_j_paxton and @micoolcho now to learn more!
Unitree Embodied AI Model Manufactures Robots in Factory🤩 Based on Unitree’s UnifoLM-X1-0 embodied AI model, this is an actual deployment at Unitree’s own robot factory.
Me defending my O(n^3) solution to the coding interviewer.
#CoRL2024 IMAGINATION POLICY: Using Generative Point Cloud Models for Learning Manipulation Policies Led by @HaojieHuang13. A key-frame multi-task policy can generate key poses (imagine) and do manipulation precisely with sample efficiency. Presenting at Poster Session 4.
