Prof. Changyue Song on “Data Science for Status Inference and Prediction in Smart and Connected Systems”
From Edmund Fogarty II
Presented on Wednesday, October 14, 2020 for the SSE Dean’s Virtual Seminar Series: The Future of Systems, featuring Prof. Changyue Song on "Data Science for Status Inference and Prediction in Smart and Connected Systems."
In this talk, Prof. Song focuses on data science for status inference and prediction in smart and connected systems with specific applications in crowdsourcing and predictive maintenance. He will discuss a novel statistical model to simultaneously detect collusion, learn workers’ expertise and infer the correct labels by treating workers in a pairwise manner. He will also talk about condition monitoring and predictive maintenance.
Dr. Song is an assistant professor in the School of Systems and Enterprises. He received his Ph.D. from the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison. His research interest lies in data science and system informatics, with a recent focus on status inference and prediction in smart systems.
The series has been created to keep students informed on the advances of faculty research, and the mission of the School of Systems and Enterprises as a leader in systems science and engineering. Each lecture will be recorded and made available on the School of Systems and Enterprises Kaltura channel for those who are unable to attend the live Zoom sessions.