工作简历

2011.09 - 2015.06.18，南京航空航天大学，本科

毛航宇研究方向为强化学习、大模型智能体系统及芯片架构。在人工智能顶会和顶刊上发表论文 50 余篇，申请专利 10 余项，作为负责人和核心骨干承担 10 余项国家自然科学基金项目、中国科学院引才项目、千万级别企业内部项目、校企合作项目等，获多项省部级及以上奖励。长期担任人工智能顶会的高级程序委员会委员、地方政府智库专家；曾在多家高科技互联网企业担任研发团队负责人，具备丰富的产业落地经验，主导开发的大模型智能体系统实现超千万的用户规模及月活。

强化学习、智能体与多智能体系统、大模型、AI 芯片与系统

全部论文参考谷歌学术：  

https://scholar.google.com/citations?user=EtVHsgcAAAAJ

本人指导的学生一作/本人二作或共同一作（5 篇代表作）：  

1. Guanting Dong*, Hangyu Mao*, Kai Ma, Licheng Bao, Yifei Chen, Zhongyuan  

Wang, Zhongxia Chen, Jiazhen Du, Huiyang Wang, Fuzheng Zhang, Guorui Zhou,  

Yutao Zhu, Ji-Rong Wen, and Zhicheng Dou. Agentic Reinforced Policy  

Optimization. ICLR 2026.

2. Bin Zhang, Hangyu Mao, Lijuan Li, Zhiwei Xu, Dapeng Li, Rui Zhao, and Guoliang  

Fan. Sequential Asynchronous Action Coordination in Multi-Agent Systems: A  

Stackelberg Decision Transformer Approach. ICML 2024 (CCF-A).

3. Yiqun Chen, Hangyu Mao, Jiaxin Mao, Shiguang Wu, Tianle Zhang, Bin Zhang, Wei  

Yang, and Hongxing Chang. PTDE: Personalized Training with Distilled Execution  

for Multi-Agent Reinforcement Learning. IJCAI 2024 (CCF-A).

4. Mingzhe Xing, Hangyu Mao, Shenglin Yin, Lichen Pang, Zhengchao Zhang, Zhen  

Xiao, and Jieyi Long. A Dual-Agent Scheduler for Distributed Deep Learning Jobs  

on Public Cloud via Reinforcement Learning. KDD 2023 (CCF-A).

5. Mingzhe Xing, Hangyu Mao, and Zhen Xiao. Fast and Fine-grained Autoscaler for  

Streaming Jobs with Reinforcement Learning. IJCAI 2022 (CCF-A)