Structural Health Monitoring, Uncertainty Quantification, Time Series Analysis, Surrogate Modeling, Haptic Decision-Making, Intelligent Infrastructure and Sustainability
Structural health monitoring (SHM) and non-destructive evaluation (NDE); Uncertainty quantification; Time series modeling and signal processing; Surrogate modeling of complex systems; Machine learning and Bayesian inference regarding SHM decision-makings; Cyber-physical systems, haptics and human machine interaction
Zhu Mao is currently an Assistant Professor of Mechanical Engineering at the University of Massachusetts Lowell, and has actively worked in the area of structural health monitoring and uncertainty quantification for nearly ten years. Prior to UMass Lowell, he held research positions at the Tsinghua University and Hong Kong Polytechnic University, and then joined University of California San Diego as a research assistant and later a postdoctoral researcher. His research aims to enhance the system integrity and infrastructure sustainability, and the research effort embodies the emerging nexus of multiple disciplines, including mechanical, aerospace and civil applications. His research is sponsored by a variety of resources, and he collaborates with colleagues at US Air Force Research Lab, Army Research Lab, Los Alamos National Lab, and South Korea Agency for Defense Development, as well as university researchers all over the world. Mao has over 30 publications on top-tier journals and internationally-recognized conference proceedings. He has been invited to coauthor one book chapter about uncertainty quantification in SHM. Additionally, Dr. Mao is active in numerous professional communities, and serves on the committee of the Technical Division of Model Validation and Uncertainty Quantification in the Society for Experimental Mechanics. He has been the reviewer for 18 journals, and serves as session chair for multiple conferences. He was awarded the DeMichele Scholarship Award by the Society for Experimental Mechanics in 2011.