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Liu Cao

Hello there! I'm Liu Cao, currently a first-year PhD student in IIIS, Tsinghua University, advised by Prof. Mengdi Xu on Humanoid Robots and Whole-body Control. Before that, I received my bachelor's degree from EE, Tsinghua University.

My current interests lie in developing autonomous robots, particularly humanoid and mobile manipulators, capable of active perception and interacting in the real-world scenarios.

Research

Fine-Tuning Hard-to-Simulate Objectives for Quadruped Locomotion: A Case Study on Total Power Saving
Ruiqian Nai, Jiacheng You, Liu Cao, Hanchen Cui, Shiyuan Zhang, Huazhe Xu, Yang Gao,
IEEE International Conference on Robotics and Automation (ICRA), 2025
project page / arXiv

Better locomotion using real-world data. Our approach achieves a 24-28% net reduction in power consumption

Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response
Junfeng Long^*, Zirui Wang^*, Quanyi Li, Jiawei Gao, Liu Cao, Jiangmiao Pang
^*Equal contribution
International Conference on Learning Representations (ICLR), 2024
project page / arXiv

We present the Hybrid Internal Model, a method enabling the control policy to estimate environmental disturbances by only explicitly estimating velocity and implicitly simulating the system's response.

Detecting Vulnerable Nodes in Urban Infrastructure Interdependent Network
Jinzhu Mao^*, Liu Cao^*, Chen Gao, Huandong Wang, Hangyu Fan, Depeng Jin, Yong Li
^*Equal contribution
ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD), 2023
code / arXiv

We model the interdependent network as a heterogeneous graph and propose a system based on graph neural network with reinforcement learning, which can be trained on real-world data, to characterize the vulnerability of the city system accurately.

Website template from Jon Barron.