Dr. Yun-Bo Zhao（赵云波)

Department of Automation

University of Science and Technology of China

Hefei, China

Email: ybzhao@ustc.edu.cn

The Networked Intelligent Control Lab (网络化智能控制实验室，“NIC Lab”) is led by Prof. Yun-Bo Zhao（赵云波) with Department of Automation & Institute of Advanced Technology, University of Science and Technology of China, Hefei, China（中国科学技术大学自动化系 & 先进技术研究院), and also with Institute of Artificial Intelligence, Hefei Comprehensive National Science Center (合肥综合性国家科学中心人工智能研究院).

The NIC Lab is generally interested in the following research fields.

  • AI驱动的网络化智能控制AI-Driven Networked Intelligent Control: 无线网络下控制和通信的联合设计及系统安全、大数据驱动的无模型控制和“云管端”新通信模式下控制系统的架构分析等理论问题，及在智慧工厂、智慧物流、绿色建筑、特种移动机器人等领域的应用。The co-design of wireless networked control systems and its security, Big Data driven control, cloud control, and relevant applications in smart factory, smart logistics, green building, dedicated mobile robots, etc.

  • AI驱动的可靠智造AI-Driven Reliable Smart Manufacturing: 非可信的人工智能在智能制造场景下的系统性分析，满足可靠保证的工业人工智能基本方法，和典型工业场景下的可靠智造关键技术和应用示范。Systematic analysis of unreliable AI in the smart manufacturing context, fundamental methodologies of reliable industry AI, and key technologies of reliable smart manufacturing for typical industry scenarios.

  • AI驱动的人机混合智能AI-Driven Human-Machine Hybrid Intelligence: 面向自动化控制的人机混合智能基本理论和方法，包括人机自主性和人机信任的量化和分析，人机控制中的介入和共享控制基本方法，和人机对抗中的人机博弈基础模型和策略等方面，及其在人机共驾、复杂空战人机对抗、智能制造等领域的应用。The fundamental theory and methodologies of control-oriented human-machine hybrid intelligence, including aspects such as the quantization and analysis of autonomy and trust in the human-machine context, the fundamental methodology of traded and shared control, and the models and strategies in human-machine games, as well as relevant applications in human-machine co-drive, human-UAV confrontation, smart manufacturing, etc.

Prospective Master and PhD students are always welcome to join the NIC Lab. Please feel free to drop an email if interested.

欢迎有志于从事人工智能、自动化等相关领域学习和研究的博士、硕士和优秀本科生加入我们的研究团队。如需更多信息，可发邮件联系，也可先与实验室现有成员联系了解。