Ziqi Wang

Wang's research focuses on analyzing and understanding the reliability, risk, and resilience of structures and critical infrastructures under hazards. He is also interested in applying probabilistic methods to a broader field of science. Here are a few of the research areas Wang is currently working on:

Reliability and Uncertainty Quantification methods leveraging domain/problem-specific knowledge

The hypothesis is that an optimal (e.g., efficient, accurate, interpretable, scalable, general) computational method does not exist if a wide spectrum of problems is considered; the domain knowledge should be injected into the design of computational methods for a particular class of problems. 

• [2310.00261] A physics and data co-driven surrogate modeling method for high-dimensional rare event simulation (arxiv.org)
• [2303.13023] Relaxation-based importance sampling for structural reliability analysis (arxiv.org)
• [2304.06252] Adaptive active subspace-based metamodeling for high-dimensional reliability analysis (arxiv.org)
• [2208.08991] Optimized Equivalent Linearization for Random Vibration (arxiv.org)
• [2310.10232] Efficient seismic reliability and fragility analysis of lifeline networks using subset simulation (arxiv.org)

Probabilistic approaches for analyzing the regional-scale impact of natural hazards

Statistical physics and information-theoretic approaches in modeling and analyzing the collective behaviors of networked structures under natural hazards.

• [2310.17798] Maximum entropy-based modeling of community-level hazard responses for civil infrastructures (arxiv.org)
• Determination of Recovery Bridges through Post-earthquake Corridor Identification (PEER Annual Meeting)

Other research activities related to probabilistic methods 

Stochastic dynamics of disasters.

• [2007.04136] The dynamics of entropy in the COVID-19 outbreaks (arxiv.org)
• (in Chinese) https://www.bilibili.com/video/BV1wY4y1y7aX/?spm_id_from=333.999.0.0
• Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database | PLOS ONE