To the future of Reinforcement learning and embodied AI.
Short Bio
Zheng Ziang is a master’s student at the Intelligent Driving Lab, School of Vehicle and Mobility, Tsinghua University. He earned his bachelor’s degree in IoT Engineering from the School of Computer Science, Central South University, graduating first in his class. His research interests include reinforcement learning, imitation learning, embodied AI, and autonomous driving, with strong expertise in algorithm development and model training. Skilled in Linux environments and embedded systems, he has contributed to impactful research projects, published academic papers, and submitted work to top-tier conferences. With a passion for solving challenging research problems, Zheng thrives in teamwork and interdisciplinary innovation. His achievements include numerous awards, such as national scholarships and honors in provincial-level competitions.
Looking for Opportunities
Zheng is open to deep collaborations and actively seeking internship opportunities.
Feel free to reach out via email: ziang_zheng@foxmail.com.
Publications
Canonical Form of Datatic Description in Control Systems
Guojian Zhan, Ziang Zheng, Shengbo Li, "Canonical Form of Datatic Description in Control Systems." arXiv preprint arXiv:2403.01768, 2024.
Adaptive device sampling and deadline determination for cloud-based heterogeneous federated learning
Deyu Zhang, Wang Sun, Zi-Ang Zheng, Wenxin Chen, Shiwen He, "Adaptive device sampling and deadline determination for cloud-based heterogeneous federated learning." Journal of Cloud Computing, 2023.