Zhiyuan Zhang 张志远

Email: zhan5570 AT purdue.edu

I'm a first-year PhD student at Purdue University, advised by Professor Yu She. I was honored with the IE Graduate Excellence Award at Purdue University.

I received my Bachelor's and Master's degrees in Mechanical Engineering from Huazhong University of Science and Technology.

G. Scholar  /  Twitter  /  Github  /  LinkedIn

News

Research

* indicates equal contribution.

My research aims to design learning algorithms for robotic agents, enabling them to perform everyday manipulation tasks with human-level proficiency. To this end, I am currently focusing on hierarchical multimodal robot learning. Specifically, my research explores:

1. Integrating visual, 3D, and tactile modalities to enable multimodal robot learning.
2. Developing interpretable neural-symbolic low-level policies through differentiable optimization.
3. Deploying pretrained vision-language models for high-level, open-world reasoning and planning.

Canonical Policy: Learning Canonical 3D Representation for Equivariant Policy
Zhiyuan Zhang*, Zhengtong Xu*, Jai Nanda Lakamsani, Yu She
Under Review, 2025

Canonical Policy enables equivariant observation-to-action mappings by grouping both in-distribution and out-of-distribution point clouds to a canonical 3D representation.

ManiFeel: Benchmarking and Understanding Visuotactile Manipulation Policy Learning
Quan Khanh Luu*, Pokuang Zhou*, Zhengtong Xu*, Zhiyuan Zhang, Qiang Qiu, Yu She
Under Review, 2025

ManiFeel is a reproducible and scalable simulation benchmark for studying supervised visuotactile policy learning.

GelRoller: A Rolling Vision-based Tactile Sensor for Large Surface Reconstruction Using Self-Supervised Photometric Stereo Method
Zhiyuan Zhang, Huan Ma, Yulin Zhou, Jingjing Ji, Hua Yang
ICRA, 2024

                    @INPROCEEDINGS{10610417,
                      author={Zhang, Zhiyuan and Ma, Huan and Zhou, Yulin and Ji, Jingjing and Yang, Hua},
                      booktitle={2024 IEEE International Conference on Robotics and Automation (ICRA)}, 
                      title={GelRoller: A Rolling Vision-based Tactile Sensor for Large Surface Reconstruction Using Self-Supervised Photometric Stereo Method}, 
                      year={2024},
                      volume={},
                      number={},
                      pages={7961-7967},
                      keywords={Mechanical sensors;Surface reconstruction;Accuracy;Shape;Shape measurement;Tactile sensors;Lighting},
                      doi={10.1109/ICRA57147.2024.10610417}}
                  

By leveraging GelRoller, users can quickly sense large surfaces and reconstruct the 3D shape of the contact region using just a single input image.

Awards

• IE Graduate Excellence Award, Purdue University, 2025
• Digital Electronics Scholarship, Huazhong University of Science and Technology, 2023
• Xiaomi Scholarship, Huazhong University of Science and Technology, 2020

Website template from Jon Barron's website.