Welcome to the Risk Assessment and Mitigation (RAM) Lab at Colorado State University

Evaluating risks and enhancing infrastructure resilience under different types of hazards pose a great challenge, especially considering the fact that infrastructure systems are now composed of interconnected systems/networks exposed to multiple hazards over their lifetime. Deterioration effects of the aging infrastructure systems as well as time-varying characteristics of environmental conditions and hazards (for example due to climate change) further increase the complexity of this problem. Uncertainty quantification/propagation plays an essential role for addressing this challenge as exposure to hazards and necessity to perform life-cycle analysis introduce significant sources of variability in our models for assessing performance/resilience. Unfortunately, reliance on traditional approaches for these tasks is being proven inadequate for tackling this challenge, forcing frequently modeling simplifications that do not faithfully capture the behaviors of interest.

To address these challenges, the RAM Lab at Colorado State University is developing generalized simulation-based approaches that can facilitate efficient risk assessment and mitigation for infrastructure system. The research in the RAM Lab leverages the versatility of generalized simulation-based approaches and the efficiency of soft computing and high performance computing to address challenges associated with solving complex engineering systems. The ultimate goal of the research is to deliver a powerful, versatile framework for risk assessment/mitigation that is applicable for a variety of hazards, can accommodate models with high degree of complexity, and can also provide enhanced decision support even for real-time applications.

Research areas in the RAM Lab include:

  • (Real-time) Natural hazard risk assessment and mitigation
  • Surrogate modeling for efficient analysis and design of complex engineering systems
  • Life-cycle cost analysis and design of high performance engineering systems
  • Stochastic optimization, uncertainty quantification, advanced stochastic simulation
  • Modeling of aging and deterioration of infrastructure systems
  • Earthquake engineering, structural dynamics, seismic protective systems
  • Multi-hazard analysis
  • Bayesian approaches for model validation, condition assessment of critical infrastructure
  • Risk-informed decision making


Recent News: Ph.D. student positions available for Spring and Fall 2018!

The RAM Lab is seeking highly motivated Ph.D. students starting Spring or Fall 2018. Interested applicants are encouraged to contact Dr. Gaofeng Jia (Gaofeng.Jia@colostate.edu) and send your full CV (with GPAs, GRE/TOEFL scores etc.).

Student News:

  • Zhenqiang Wang joins RAM Lab as a Ph.D. student starting June 2017. Welcome!
  • Jeet Kumar Sonwani joins RAM Lab as a Master student. Welcome!