Linxia Liao’s research interests include predictive and prescriptive analytics; system and components fault diagnostics and prognostics; signal processing; and machine learning algorithms as well as their integration on embedded systems. Currently, he is developing device fleet health management solutions for intelligent transportation systems.
Prior to joining PARC, Linxia worked as a research scientist with Siemens Corporate, Corporate Technology (previous Siemens Corporate Research) located in Princeton, NJ. He conducted research and implemented various prognostics and health management-related applications in the fields of manufacturing, energy, and transportation. He also previously worked at Siemens Technology-To-Business (TTB) Center in Berkeley, CA to transfer the patented ‘Methods for prognosing mechanical systems’ technology from the university to industry applications.
Dr. Liao received his Ph.D. degree in Industrial Engineering from the University of Cincinnati, where he conducted research at the NSF I/UCR Center for Intelligent Maintenance Systems (IMS). He earned his M.S. and B.S. degrees in Mechanical Science and Engineering at Huazhong University of Science and Technology (HUST) in China. Linxia has one issued patent and seven pending patents, and he has published one book chapter and 20+ papers in leading journals and conferences.
Linxia enjoys cycling and hiking around the Bay Area.