Sungjae Park

Hi, I am a M.S. in Robotics student at Carnegie Mellon University, advised by Prof. Shubham Tulsiani.

Previously, I was a research intern in the Visual Computing lab at Seoul National University, advised by Prof. Hanbyul Joo. I also spent time in CLVR lab at KAIST, advised by Prof. Joseph J. Lim. I completed B.S. (Summa Cum Laude) in Mechanical Engineering and Mathematics at Seoul National University.

Email  /  CV  /  Twitter  /  Github

My research goal is to develop a robot with human-like abilities, including physical capabilities for manipulation tasks, and cognitive capabilities for intuitive understanding of the real world.

Specifically, I am interested in solving complex manipulation tasks (e.g. dexterous, contact-rich, long-horizon tasks),
physical reasoning WITH interaction (e.g. experimenting with objects and inferring properties with physical interaction), and
physical reasoning FOR interaction(e.g. intuitive physics, leveraging object permanence for efficient object retrieval).

* denotes equal contribution.

We learn object centric trajectory planner from different robot's demonstration for cross-embodiment transfer.

We combine gaussian process motion planning with entropy-based information factor to perform online active motion planning in unknown environments.

We learn reachable manifold of franka panda robot arm with block neural autoregressive flow as in Kim et al. , and perform contrained motion planning directly in the learned latent space.

We perform robust peg insertion with YOLO-v3 based hole/box detection model.

Reviewer for NeurIPS 2023, ICLR 2024.