Zhipeng Zhao is a PhD student at the Department of Computer Science and Engineering (CSE), University at Buffalo (UB). His research interests involve robot perception and neuro-symbolic AI. He has received a Chair’s Fellowship.

Education

Ph.D. in Computer Science
- University at Buffalo (UB), USA
- 2023 - Present
Bachelor of Engineering in Electronic Information Engineering
- Wuhan University, Wuhan, China
- Sep. 2018 - June 2023

Awards

Chair’s Fellowship

Other Information

Work Email: zhipengz@sairlab.org
School Email: zzhao43@buffalo.edu

Publications

Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy.
Chen Wang, Kaiyi Ji, Junyi Geng, Zhongqiang Ren, Taimeng Fu, Fan Yang, Yifan Guo, Haonan He, Xiangyu Chen, Zitong Zhan, Qiwei Du, Shaoshu Su, Bowen Li, Yuheng Qiu, Yi Du, Qihang Li, Yifan Yang, Xiao Lin, Zhipeng Zhao.
International Journal of Robotics Research (IJRR), 2025.

Unifying Neuro-Symbolic Robot Autonomy via a Unified Paradigm
```
@article{wang2025imperative,
  title = {Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy},
  author = {Wang, Chen and Ji, Kaiyi and Geng, Junyi and Ren, Zhongqiang and Fu, Taimeng and Yang, Fan and Guo, Yifan and He, Haonan and Chen, Xiangyu and Zhan, Zitong and Du, Qiwei and Su, Shaoshu and Li, Bowen and Qiu, Yuheng and Du, Yi and Li, Qihang and Yang, Yifan and Lin, Xiao and Zhao, Zhipeng},
  journal = {International Journal of Robotics Research (IJRR)},
  year = {2025},
  url = {https://arxiv.org/abs/2406.16087},
  code = {https://github.com/sair-lab/iSeries},
  website = {https://sairlab.org/iseries},
  addendum = {Unifying Neuro-Symbolic Robot Autonomy via a Unified Paradigm}
}
```
```
Wang, Chen and Ji, Kaiyi and Geng, Junyi and Ren, Zhongqiang and Fu, Taimeng and Yang, Fan and Guo, Yifan and He, Haonan and Chen, Xiangyu and Zhan, Zitong and Du, Qiwei and Su, Shaoshu and Li, Bowen and Qiu, Yuheng and Du, Yi and Li, Qihang and Yang, Yifan and Lin, Xiao and Zhao, Zhipeng, "Imperative Learning: A Self-supervised Neuro-Symbolic Learning Framework for Robot Autonomy," International Journal of Robotics Research (IJRR), 2025.
```
SuperPC: A Single Diffusion Model for Point Cloud Completion, Upsampling, Denoising, and Colorization.
Yi Du, Zhipeng Zhao, Shaoshu Su, Sharath Golluri, Haoze Zheng, Runmao Yao, Chen Wang.
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 16953–16964, 2025.
```
@inproceedings{du2025superpc,
  title = {{SuperPC}: A Single Diffusion Model for Point Cloud Completion, Upsampling, Denoising, and Colorization},
  author = {Du, Yi and Zhao, Zhipeng and Su, Shaoshu and Golluri, Sharath and Zheng, Haoze and Yao, Runmao and Wang, Chen},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  url = {https://arxiv.org/abs/2503.14558},
  website = {https://sairlab.org/superpc/},
  year = {2025},
  pages = {16953--16964}
}
```
```
Du, Yi and Zhao, Zhipeng and Su, Shaoshu and Golluri, Sharath and Zheng, Haoze and Yao, Runmao and Wang, Chen, "SuperPC: A Single Diffusion Model for Point Cloud Completion, Upsampling, Denoising, and Colorization," IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
```
Fast Task Planning with Neuro-Symbolic Relaxation.
Qiwei Du, Bowen Li, Yi Du, Shaoshu Su, Taimeng Fu, Zitong Zhan, Zhipeng Zhao, Chen Wang.
arXiv preprint arXiv:2507.15975, 2025.
```
@article{du2025fast,
  title = {Fast Task Planning with Neuro-Symbolic Relaxation},
  author = {Du, Qiwei and Li, Bowen and Du, Yi and Su, Shaoshu and Fu, Taimeng and Zhan, Zitong and Zhao, Zhipeng and Wang, Chen},
  year = {2025},
  journal = {arXiv preprint arXiv:2507.15975},
  url = {https://arxiv.org/abs/2507.15975},
  website = {https://sairlab.org/flax/},
  video = {https://youtu.be/_4DYcqwycnQ}
}
```
```
Du, Qiwei and Li, Bowen and Du, Yi and Su, Shaoshu and Fu, Taimeng and Zhan, Zitong and Zhao, Zhipeng and Wang, Chen, "Fast Task Planning with Neuro-Symbolic Relaxation," arXiv preprint arXiv:2507.15975, 2025.
```
VL-Nav: Real-time Vision-Language Navigation with Spatial Reasoning.
Yi Du, Taimeng Fu, Zhuoqun Chen, Bowen Li, Shaoshu Su, Zhipeng Zhao, Chen Wang.
arXiv preprint arXiv:2502.00931, 2025.

SAIR Lab Selected
```
@article{du2025vlnav,
  title = {{VL-Nav}: Real-time Vision-Language Navigation with Spatial Reasoning},
  author = {Du, Yi and Fu, Taimeng and Chen, Zhuoqun and Li, Bowen and Su, Shaoshu and Zhao, Zhipeng and Wang, Chen},
  year = {2025},
  journal = {arXiv preprint arXiv:2502.00931},
  url = {https://arxiv.org/abs/2502.00931},
  website = {https://sairlab.org/vlnav/},
  addendum = {SAIR Lab Selected}
}
```
```
Du, Yi and Fu, Taimeng and Chen, Zhuoqun and Li, Bowen and Su, Shaoshu and Zhao, Zhipeng and Wang, Chen, "VL-Nav: Real-time Vision-Language Navigation with Spatial Reasoning," arXiv preprint arXiv:2502.00931, 2025.
```
AnyNav: Visual Neuro-symbolic Friction Learning for Off-road Navigation.
Taimeng Fu, Zitong Zhan, Zhipeng Zhao, Shaoshu Su, Xiao Lin, Ehsan Tarkesh Esfahani, Karthik Dantu, Souma Chowdhury, Chen Wang.
arXiv preprint arXiv:2501.12654, 2025.

SAIR Lab Selected
```
@article{fu2025anynav,
  title = {{AnyNav}: Visual Neuro-symbolic Friction Learning for Off-road Navigation},
  author = {Fu, Taimeng and Zhan, Zitong and Zhao, Zhipeng and Su, Shaoshu and Lin, Xiao and Esfahani, Ehsan Tarkesh and Dantu, Karthik and Chowdhury, Souma and Wang, Chen},
  journal = {arXiv preprint arXiv:2501.12654},
  year = {2025},
  url = {https://arxiv.org/abs/2501.12654},
  website = {https://sairlab.org/anynav/},
  addendum = {SAIR Lab Selected}
}
```
```
Fu, Taimeng and Zhan, Zitong and Zhao, Zhipeng and Su, Shaoshu and Lin, Xiao and Esfahani, Ehsan Tarkesh and Dantu, Karthik and Chowdhury, Souma and Wang, Chen, "AnyNav: Visual Neuro-symbolic Friction Learning for Off-road Navigation," arXiv preprint arXiv:2501.12654, 2025.
```
PhysORD: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving.
Zhipeng Zhao, Bowen Li, Yi Du, Taimeng Fu, Chen Wang.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 11670–11677, 2024.

SAIR Lab Selected
```
@inproceedings{zhao2024physord,
  title = {{PhysORD}: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving},
  author = {Zhao, Zhipeng and Li, Bowen and Du, Yi and Fu, Taimeng and Wang, Chen},
  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
  year = {2024},
  pages = {11670--11677},
  url = {https://arxiv.org/abs/2404.01596},
  code = {https://github.com/sair-lab/PhysORD},
  video = {https://youtu.be/kYa9dAyUkYI},
  website = {https://sairlab.org/physord},
  addendum = {SAIR Lab Selected}
}
```
```
Zhao, Zhipeng and Li, Bowen and Du, Yi and Fu, Taimeng and Wang, Chen, "PhysORD: A Neuro-Symbolic Approach for Physics-infused Motion Prediction in Off-road Driving," IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2024.
```
PyPose v0.6: The Imperative Programming Interface for Robotics.
Zitong Zhan, Xiangfu Li, Qihang Li, Haonan He, Abhinav Pandey, Haitao Xiao, Yangmengfei Xu, Xiangyu Chen, Kuan Xu, Kun Cao, Zhipeng Zhao, Zihan Wang, Huan Xu, Zihang Fang, Yutian Chen, Wentao Wang, Xu Fang, Yi Du, Tianhao Wu, Xiao Lin, Yuheng Qiu, Fan Yang, Jingnan Shi, Shaoshu Su, Yiren Lu, Taimeng Fu, Karthik Dantu, Jiajun Wu, Lihua Xie, Marco Hutter, Luca Carlone, Sebastian Scherer, Daning Huang, Yaoyu Hu, Junyi Geng, Chen Wang.
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Workshop, 2023.
```
@inproceedings{zhan2023pypose,
  title = {{PyPose} v0.6: The Imperative Programming Interface for Robotics},
  author = {Zhan, Zitong and Li, Xiangfu and Li, Qihang and He, Haonan and Pandey, Abhinav and Xiao, Haitao and Xu, Yangmengfei and Chen, Xiangyu and Xu, Kuan and Cao, Kun and Zhao, Zhipeng and Wang, Zihan and Xu, Huan and Fang, Zihang and Chen, Yutian and Wang, Wentao and Fang, Xu and Du, Yi and Wu, Tianhao and Lin, Xiao and Qiu, Yuheng and Yang, Fan and Shi, Jingnan and Su, Shaoshu and Lu, Yiren and Fu, Taimeng and Dantu, Karthik and Wu, Jiajun and Xie, Lihua and Hutter, Marco and Carlone, Luca and Scherer, Sebastian and Huang, Daning and Hu, Yaoyu and Geng, Junyi and Wang, Chen},
  year = {2023},
  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Workshop},
  url = {https://arxiv.org/abs/2309.13035},
  code = {https://github.com/pypose/pypose},
  video = {https://youtu.be/XDtUDIWuGng},
  website = {https://sairlab.org/pypose/}
}
```
```
Zhan, Zitong and Li, Xiangfu and Li, Qihang and He, Haonan and Pandey, Abhinav and Xiao, Haitao and Xu, Yangmengfei and Chen, Xiangyu and Xu, Kuan and Cao, Kun and Zhao, Zhipeng and Wang, Zihan and Xu, Huan and Fang, Zihang and Chen, Yutian and Wang, Wentao and Fang, Xu and Du, Yi and Wu, Tianhao and Lin, Xiao and Qiu, Yuheng and Yang, Fan and Shi, Jingnan and Su, Shaoshu and Lu, Yiren and Fu, Taimeng and Dantu, Karthik and Wu, Jiajun and Xie, Lihua and Hutter, Marco and Carlone, Luca and Scherer, Sebastian and Huang, Daning and Hu, Yaoyu and Geng, Junyi and Wang, Chen, "PyPose v0.6: The Imperative Programming Interface for Robotics," IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Workshop, 2023.
```
Attention-Enhanced Cross-modal Localization Between Spherical Images and Point Clouds.
Zhipeng Zhao, Huai Yu, Chenwei Lyu, Wen Yang, Sebastian Scherer.
IEEE Sensors Journal, 2023.
```
@article{zhao2023attention,
  title = {Attention-Enhanced Cross-modal Localization Between Spherical Images and Point Clouds},
  author = {Zhao, Zhipeng and Yu, Huai and Lyu, Chenwei and Yang, Wen and Scherer, Sebastian},
  journal = {IEEE Sensors Journal},
  year = {2023},
  url = {https://ieeexplore.ieee.org/abstract/document/10227896},
  video = {https://youtu.be/zZKu1I8Xbb8?si=yd5CtLmkowBe-OZM},
  code = {https://github.com/Zhaozhpe/AE-CrossModal},
  publisher = {IEEE}
}
```
```
Zhao, Zhipeng and Yu, Huai and Lyu, Chenwei and Yang, Wen and Scherer, Sebastian, "Attention-Enhanced Cross-modal Localization Between Spherical Images and Point Clouds," IEEE Sensors Journal, 2023.
```