Please join us in welcoming Shiyu Zhou, the Vilas Distinguished Achievement Professor at the University of Wisconsin-Madison, as he discusses events data analytics for smart systems.
Event Data Analytics for Smart Systems
With the rapid development of information technology, an abundance of data that record the events that occurred in an engineering system are now collected automatically. The event data provide rich information regarding the system and could be used for system monitoring, prediction, and optimal operations decision making. This talk will present the recent research works in (1) Multioutput Gaussian Process Modulated Poisson Processes for Event Prediction, in which an inhomogeneous Poisson process is established and used for the prediction of recurring events, And (2) Modeling and Prediction of Multi-type Events in Presence of Censoring, in which the relationship among multiple types of events are modeled and used for the prediction of a future event. Both works provide exciting ways for future event prediction.
Shiyu Zhou is a Vilas Distinguished Achievement Professor in the Department of Industrial and Systems Engineering at the University of Wisconsin-Madison. He received his B.S. degree from the University of Science and Technology of China in 1993, and his master’s degree and Ph.D. from the University of Michigan in 2000. His research focuses on industrial data analytics and system informatics methodologies for quality and productivity improvement and operation optimization. He has received numerous research awards and grants from various federal agencies. He is currently the director of the IoT Systems Research Center at the College of Engineering of UW-Madison. He is a Fellow of IISE, ASME, and SME.
