Yuxing Wang (王昱兴)

您好 Привет Hello Bonjour Ciao こんにちは 안녕하세요 Hallo Hola

As a researcher in Embodied AI, my passion lies in Robot Co-Design, Evolutionary Learning, and Large Models. I focus on the simultaneous coordination of controlling brain, body morphology, and task environment to design embodied agents that are not only structurally sound but also behaviorally adept (Design a machine that can design other machines).

I received the B.Eng. degree from Southwest Minzu University, P.R. China, in 2020, and the M.Eng. degree from Tsinghua University, P.R. China, in 2023 (advised by Prof. Xueqian Wang). Currently, I am pursuing my Ph.D. degree in Control Science and Engineering at Tsinghua University. My industry experience includes being a research intern at Tencent AI Lab from May 2022 to May 2023, where I collaborated with Shuang Wu and Haobo Fu. My internship was supported by the 2022 Tencent Rhino-Bird Research Elite Program, and my work focused on generating user-specified behavioral diversity for Game AI.

My favorite singer is Hikaru Utada. I also like watching comedies and talk shows. Feel free to drop me an email if you are interested in my research or related ideas .

Visitors

News

Dec 01, 2025	Our survey “Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges” is publicly available on Arxiv!
Aug 01, 2025	Served as a reviewer for ICLR 2026 and AAAI 2026.
May 01, 2025	Two papers got accepted to International Astronautical Congress (IAC) 2025. See you in Sydney-Australia!
Mar 10, 2025	Served as a program committee for NeurIPS 2025 and ACMMM 2025.
Jan 01, 2025	A site of our survey “Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges” has been created. The repo will be updated on a regular basis! The full paper will be updated to Arxiv soon!
Dec 25, 2024	Served as a program committee for ICML 2025.
Aug 07, 2024	Served as a program committee for AAAI 2025 and ICLR 2025.

Selected Publications

Survey

Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges

Yuxing Wang, Zhiyu Chen, Tiantian Zhang, Qiyue Yin, Yongzhe Chang, Zhiheng Li, Liang Wang, and Xueqian Wang

Arxiv (Survey), 2025

Preprint arXiv Bib

@article{wang2025survey,
  title = {Embodied Co-Design for Rapidly Evolving Agents: Taxonomy, Frontiers, and Challenges},
  author = {Wang, Yuxing and Chen, Zhiyu and Zhang, Tiantian and Yin, Qiyue and Chang, Yongzhe and Li, Zhiheng and Wang, Liang and Wang, Xueqian},
  journal = {Arxiv},
  year = {2025},
  google_scholar_id = {roLk4NBRz8UC},
}

IAC

Morphology and Behavior Co-Optimization of Modular Satellites for Attitude Control

Yuxing Wang, Jie Li, Cong Yu, Xinyang Li, Simeng Huang, Yongzhe Chang, Xueqian Wang, and Bin Liang

The 75th International Astronautical Congress (IAC), 2024

EI, Oral Presentation arXiv Bib

Top conference

@article{wang2024morphology,
  title = {Morphology and Behavior Co-Optimization of Modular Satellites for Attitude Control},
  author = {Wang, Yuxing and Li, Jie and Yu, Cong and Li, Xinyang and Huang, Simeng and Chang, Yongzhe and Wang, Xueqian and Liang, Bin},
  journal = {The 75th International Astronautical Congress},
  year = {2024},
  google_scholar_id = {eQOLeE2rZwMC},
}

TNNLS

Dynamics-adaptive continual reinforcement learning via progressive contextualization

Tiantian Zhang, Zichuan Lin, Yuxing Wang, Deheng Ye, Qiang Fu, Wei Yang, Xueqian Wang, Bin Liang, Bo Yuan, and Xiu Li

IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2023

SCI arXiv Bib HTML Code

JCR Q1, IF=10.4

@article{zhang2023dynamics,
  title = {Dynamics-adaptive continual reinforcement learning via progressive contextualization},
  author = {Zhang, Tiantian and Lin, Zichuan and Wang, Yuxing and Ye, Deheng and Fu, Qiang and Yang, Wei and Wang, Xueqian and Liang, Bin and Yuan, Bo and Li, Xiu},
  journal = {IEEE Transactions on Neural Networks and Learning Systems},
  year = {2023},
  publisher = {IEEE},
  google_scholar_id = {9yKSN-GCB0IC},
}

CoRL

PreCo: Enhancing Generalization in Co-Design of Modular Soft Robots via Brain-Body Pre-Training

Yuxing Wang, Shuang Wu, Tiantian Zhang, Yongzhe Chang, Haobo Fu, Qiang Fu, and Xueqian Wang

In Conference on Robot Learning (CoRL) , 2023

EI, Oral Presentation, top 6.6% Bib HTML Code

Top conference

@inproceedings{wang2023preco,
  title = {PreCo: Enhancing Generalization in Co-Design of Modular Soft Robots via Brain-Body Pre-Training},
  author = {Wang, Yuxing and Wu, Shuang and Zhang, Tiantian and Chang, Yongzhe and Fu, Haobo and Fu, Qiang and Wang, Xueqian},
  booktitle = {Conference on Robot Learning},
  pages = {478--498},
  year = {2023},
  organization = {PMLR},
  google_scholar_id = {Tyk-4Ss8FVUC},
}

ICLR

Curriculum-based co-design of morphology and control of voxel-based soft robots

Yuxing Wang, Shuang Wu, Haobo Fu, Qiang Fu, Tiantian Zhang, Yongzhe Chang, and Xueqian Wang

In The Eleventh International Conference on Learning Representations (ICLR) , 2023

EI, Poster Bib HTML Code

Top conference

@inproceedings{wang2023curriculum,
  title = {Curriculum-based co-design of morphology and control of voxel-based soft robots},
  author = {Wang, Yuxing and Wu, Shuang and Fu, Haobo and Fu, Qiang and Zhang, Tiantian and Chang, Yongzhe and Wang, Xueqian},
  booktitle = {The Eleventh International Conference on Learning Representations},
  year = {2023},
  google_scholar_id = {IjCSPb-OGe4C},
}

InS

A surrogate-assisted controller for expensive evolutionary reinforcement learning

Yuxing Wang, Tiantian Zhang, Yongzhe Chang, Xueqian Wang, Bin Liang, and Bo Yuan

Information Sciences (InS), 2022

SCI arXiv Bib HTML Code

JCR Q1, IF=8.233

@article{wang2022surrogate,
  title = {A surrogate-assisted controller for expensive evolutionary reinforcement learning},
  author = {Wang, Yuxing and Zhang, Tiantian and Chang, Yongzhe and Wang, Xueqian and Liang, Bin and Yuan, Bo},
  journal = {Information Sciences},
  volume = {616},
  pages = {539--557},
  year = {2022},
  google_scholar_id = {qjMakFHDy7sC},
  publisher = {Elsevier},
}