The Data-informed Design and Intelligent Systems (DIDIS) Laboratory at University of Michigan – Shanghai Jiao Tong University Joint Institute is dedicated to engineering design research at the intersection of data science, system engineering and design science. The lab aims to develop data-driven and simulation-based approaches to support innovative design of products, systems and services under connectivity and complexity. Our research will promote the design and manufacturing 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 Additive Manufacturing (AM).
Particularly, our research is emphasized on:
- Data-driven design methods and manufacturing processes: use data mining to extract design insights and predict design features from open and closed datasets; optimize manufacturing processes by tracking and analyzing industrial big data.
- Design of intelligent interconnected product systems: identify key design attributes of a member product that influence the performance of the whole system; model the dynamic behavior of interconnected product systems; reinforcement learning and transfer learning in control of multi-agent systems.
- Collaborative design making in design of complex systems: use systems engineering methods, network analysis methods and graph computing to model, predict and optimize complex systems.
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 http://umji.sjtu.edu.cn/academics/graduate-program/