Peiqi Liu | 刘沛淇

I am a senior undergraduate student major in computer science at Peking University, advised by Prof. Hao Dong as a part of PKU-Agibot Lab.

Previously, I was a visiting student at MIT CSAIL, where I worked in the groups led by Prof. Leslie Pack Kaelbling and Prof. Josh Tenenbaum, advised by Jiayuan Mao. I also spent a semester on exchange at the University of California, Berkeley, and interned with the BAIR.

Always excited to discussing cool ideas and potential collaborations. Feel free to book a meeting with me!

Email  /  Github /  LinkedIn /  Book a Meeting

Profile Image

Research

My long-term research goal is to build robots that can acquire new skills as efficiently as humans, generalize across diverse tasks, and perform everyday physical labor. I am particularly interested in exploring novel algorithms and representations that improve the efficiency of robot skill acquisition and adaptation, enabling one-shot and zero-shot learning.

Now: I am working toward becoming a full-stack robotics researcher while learning both robotics algorithms and hardware.

BiDexAffordance Project Image
BiDexAffordance: Learning Collaborative Affordances for Efficient Bimanual Dexterous Grasping
Peiqi Liu, Jingwen Li, Zeyuan Chen, Yue Chen, Shuqi Zhao, Yuanpei Chen, Chenfeng Xu, Masayoshi Tomizuka, Wei Zhan, Ruihai Wu
ECCV 2026 Under Review

BiDexAffordance is a collaborative affordance-driven framework that learns object-centric, physics-grounded bimanual affordance maps to efficiently generate robust and generalizable bimanual dexterous grasps across diverse and unseen objects.

LEAP Project Image
Lifelong Experience Abstraction and Planning
Peiqi Liu, Joshua B. Tenenbaum, Leslie Pack Kaelbling, Jiayuan Mao
ICML 2025 Workshop PRAL (Oral)
Project Page / Paper

A framework for lifelong experience abstraction and planning that enables agents to learn and adapt continuously across different environments and tasks.

MO-DDN Project Image
MO-DDN: A Coarse-to-Fine Attribute-based Exploration Agent for Multi-object Demand-driven Navigation
Hongcheng Wang*, Peiqi Liu*, Wenzhe Cai, Mingdong Wu, Zhengyu Qian, Hao Dong
NeurIPS 2024
Project Page / arXiv

We propose a multi-object demand-driven navigation benchmark and train an coarse-to-fine attribute-based exploration agent to solve this task.

Experience

UC Berkeley Logo University of California, Berkeley
2025.1 - 2025.9
Intern Student at BAIR
Advisor: Chenfeng Xu, Ruihai Wu, Prof. Masayoshi Tomizuka
MIT Logo Massachusetts Institute of Technology
2024.6 - 2024.9
Visiting Student at MIT CSAIL
Advisor: Jiayuan Mao
PKU Logo Peking University (PKU)
2022.09 - Present
Undergraduate student
Research Advisor: Prof. Hao Dong

Template, Last updated: Apr 2026 © Peiqi Liu