Modern advances in sensing, data acquisition, communication, storage, etc., have provided tremendous opportunities for scientists and engineers to release the power of established domain knowledge to understand and design systems that align with reality at unprecedented precision. Possibilities now exist, e.g., for physical models of nature or engineered systems be better and quantitatively informed by measured data in terms of their parameters, identification uncertainty and variability, or even ‘data-driven’ models (e.g., artificial neural network) that exhibit prediction or operation capabilities otherwise difficult to formulate based on domain knowledge. In the maintenance and risk management of infrastructures, there is much room for development in the theory, computational algorithms, hardware technology to significantly improve capabilities for diagnosis, prognosis, planning, etc. This workshop aims at providing an international yet focused platform for researchers to share their experience and latest findings that contribute to the advance of infrastructure maintenance and risk management. Thematic topics include, but not limited to,

• -maintenance engineering, e.g., repair and reinforcement, external force identification,
  non-destructive testing, schedule optimization
• -structural health monitoring, e.g., modal/system identification, data-driven models,
  model updating, damage detection
• -reliability engineering, e.g., reliability algorithms, reliability-based design, risk management