The Data-informed Design and Intelligent Systems (DIDIS, 数据驱动设计与智能系统) Laboratory at University of Michigan – Shanghai Jiao Tong University Joint Institute is dedicated to the interdisciplinary research at the intersection of design optimization, data science, system engineering and control engineering. The lab aims to develop data-driven and simulation-based approaches to support innovative design, manufacturing and operation of products, systems and services under connectivity and complexity. Our research will promote the development of next-generation products and systems along with the emerging technological breakthroughs such as High-Speed Wireless Communication, Cyber-physical Systems, Big Data, Artificial Intelligence (AI), Virtual Reality (VR), and Smart Manufacturing.
Particularly, our research is emphasized on:
- Data-driven Design for Market Systems (面向市场的数据驱动产品设计): extract design insights and predict design trends from open and closed datasets to support product design in a highly competitive and uncertain market. Involved methods include data analytics, design optimization, text mining, graph computing, system modeling, network analysis and modeling.
- Multi-agent Systems (多智能体系统): develop efficient methods for the motion planning, collaboration and task assignment in multi-agent systems. Related topics include reinforcement learning, transfer learning, imitation learning, etc.
- Smart Manufacturing (智能制造): develop algorithms, methods and devices to support the information perception and decision-making in smart manufacturing. Related topics include robot motion planning, digital twin, and smart environment perception.
RECRUITING：Research Assistant Positions
The DIDIS lab is currently recruiting graduate research assistants. Both Ph.D. students and M.S. students are welcome to apply. If you are interested in joining us, please send Dr. Youyi Bi an email with your CV and a copy of your transcripts. To know more about our research, please read our research descriptions and select a few representative papers to read. Application procedure and frequently asked questions can be found at https://www.ji.sjtu.edu.cn/cn/admission/graduate-admission/.