Our Advisory Board plays a vital role in providing feedback and guidance to our center so that our research outputs can better serve the community. The Advisory Board comprises of experts from industry, government, and universities.
Principal Scientist in the System Sciences Lab (SSL) at PARC
Kai Goebel is a Principal Scientist in the System Sciences Lab (SSL) at PARC. His interest is systems health management and autonomy for a broad spectrum of cyber-physical systems in the transportation, energy, aerospace, defense, and manufacturing sectors. Prior to joining PARC, Dr. Goebel worked at NASA Ames Research Center where he was the Area Lead for Discovery and Systems Health where he founded the Prognostics Center of Excellence and directed work for Integrated Vehicle Health Management. Dr. Goebel started his professional career at General Electric Corporate Research & Development center where he carried out applied research in the areas of machine learning, real time monitoring, diagnostics, and prognostics. He has fielded numerous applications for aircraft engines, transportation systems, energy applications, medical systems, and manufacturing systems. Dr. Goebel has a Ph.D. from UC Berkeley in Mechanical Engineering. He holds 18 patents and has published more than 375 papers in the field. Dr. Goebel was an adjunct professor of the CS Department at Rensselaer Polytechnic Institute (RPI), Troy, NY, between 1998 and 2004 where he taught classes in Soft Computing and Applied Intelligent Reasoning Systems and is now adjunct Professor at Lulea Technical University. Dr. Goebel is a member of ASME, AAAI, AIAA, IEEE, VDI, and SAE. He was the General Chair of the Annual Conference of the PHM Society, 2009 and held numerous chair positions at the PHM conference and the AAAI Annual meetings series. He is a co-founder of the Prognostics and Health Management Society and he is currently associate editor of the International Journal of PHM. He has been elected to the board of directors of several technical and non-technical non-profit organizations.
Technology Manager for Probabilistics, Structural Optimization and Manufacturing Design Group at GE Research
Dr. Liping Wang is currently the Technology Manager for Probabilistics, Structural Optimization and Manufacturing Design Group at GE Research. She has 20+ years’ experience in the research, development and delivery of machine learning and probabilistic methods and software for design and decision making under uncertainty across GE businesses. She joined GE Global Research Center, Niskayuna in January, 1997. Since 2007, she led the team in developing state-of-the-art machine learning and probabilistic methods and tools to provide for world-class NPI and NTI and Services capabilities throughout the company. She and her team have been driving numerous engineering applications across multiple GE businesses. She has 70+ publications in archival journals and peer-reviewed conference proceedings, 60+ internal reports along with 8 patents filed.