Pingcheng Jian 简平诚

I am a final year PhD student in the ECE department at Duke University. I'm fortunate to be co-advised by Professor Michael Zavlanos and Professor Boyuan Chen.

Before joining Duke, I obtained my bachelor of engineering from the Department of Automation at Tsinghua University.

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My area of research is robot learning, and my previous publications cover the 3 topics:
1) Applying foundation models for the preference feedback in reinforcement learning,
2) Modularity for robot learning,
3) Adversarial learning for robust control.

We present Perception Stitching that enables strong zero-shot adaptation to large visual changes by directly stitching novel combinations of visual encoders.

We present LAPP (LLM-Assisted Preference Prediction), a novel framework that leverages LLMs to generate preference feedback from raw state-action trajectories that is used to guide reinforcement learning (RL) agents.

We propose Policy Stitching, a novel framework to facilitate multi-task and multi-robot transfer.

Using adversarial reinforcement learning to imrove the robustness of robotic manipulation.

We propose a physics-based method to learn environmental fields (EFs) using a mobile robot.

Solve complex bimanual robot manipulation tasks on multiple objects with disentangled attention, which provides an intrinsic regularization for two robots to focus on separate sub-tasks and objects.

Some course projects show my engineering capability.

I built all the hardware and software of this spider robot from scratch. I drew the parts of this robot with SOLIDWORKS and then printed them with 3D printer. The controller of this robot is a Raspberry Pi, and the control algorithm is written in Python. Then I generated the .urdf files of this robot and built the simulator of this robot with PyBullet.