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.

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News

  • [April 2025] I was honored with the IE Graduate Excellence Award 🎉
  • [Jan 2026] Canonical Policy was conditionally accepted to IEEE Transactions on Robotics 🎉

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.

EquiForm: Noise-Robust SE(3)-Equivariant Policy Learning from 3D Point Clouds
Zhiyuan Zhang, Yu She
Under Review, 2026

website / arXiv(Soon) / video / code(Soon)

EquiForm enables noise-robust equivariant observation-to-action mappings by correcting noise-induced geometric distortions and aligning representations under SE(3) transformations.

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

website / arXiv / video / code

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

website / arXiv / video / code

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

sym

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

paper / video / bibtex

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

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