MS54 Data Science and Big Data Analytics in Structural Safety and Reliability

Prof. Ying Lei: ylei@xmu.edu.cn

Session Chairs:
Prof. Ying Lei, Xiamen University, ylei@xmu.edu.cn
Prof. Jun Chen, Tongji University, cejchen@tongji.edu.cn

Abstract of the special session:
Recent developments in structural safety and reliability have triggered paradigm shifts in scientific research. Data science and big data analytics have raised common interests in the tasks of data collection, data cleaning, data mining, data interpretation, and data-processing. These have spurred new algorithms such as data reduction, machine learning, deep neural network, transfer learning, cloud computing, visualization and high performance computing.
The purpose of this special session is to provide a forum for the exchange of information by a wide spectrum of experts from academia and industry, exposing and discussing challenges, opportunities, and research needs for advancing the state of the art in a most impactful manner.
The special session welcomes, but is not limited to, the following topics regarding structural safety and reliability:

• Cloud computing and high performance computing;
• Artificial intelligence with machine learning/deep learning techniques;
• Physics constrained data-driven inference;
• Data cleansing, Data cleansing, Multi-source data fusion, etc.
• Sparse data and Big data in rare extreme event;
• Big data-based uncertainty quantification;
• Big data-based stochastic dynamic response and reliability analysis;
• Big data-based engineering loading modelling;