University of Michigan researchers have produced a new prediction model using longitudinal information and deep learning to better predict the return to work time for people with occupational injuries.
Business Operations and Analytics
Helping people get back to work using deep learning in the occupational health system
Xiuli Chao receives funding from J&J to develop algorithms for continuous production process
U-M IOE’s Xiuli Chao receives funding from Johnson & Johnson for a project centered on developing optimization algorithms to improve continuous production process.
Xiuli Chao receives funding to improve the efficiencies of sharing economy
U-M IOE professor, Xiuli Chao, receives funding from Didi for a project focused on improving the efficiencies of sharing economy through enhanced matching and contract design.
Mitigating uncertainties in remote computer numerical control using data-driven transfer learning
U-M IOE’s Raed Al Kontar receives research funding from Cyber-physical Systems, a National Science Foundation program, for a project centered on the refinement of computer numerical control as a cloud service.
Jessie Yang receives funding from Dell for analysis of online user-generated data
U-M IOE assistant professor, Jessie Yang, has received research funding from Dell Inc. for sentiment analysis of online user-generated data for business intelligence enrichment.
Xiuli Chao and Ruiwei Jiang receive MCubed funding for data-driven optimization of online retailing
Two U-M Industrial and Operations Engineering (IOE) researchers have received MCubed funding from the University of Michigan for work on data-driven optimization for online retailing.
