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Uncertainty is prevalent in engineering design, data-driven problems, and decision making broadly. Due to inherent risk-averseness and ambiguity about assumptions, it is common to address uncertainty by formulating and solving conservative…
Regional disaster resilience quantifies the changing nature of physical risks to inform policy instruments ranging from local immediate recovery to international sustainable development. While many existing state-of-practice methods have…
Technologies such as aerial photogrammetry allow production of 3D topographic data including complex environments such as urban areas. Therefore, it is possible to create High Resolution (HR) Digital Elevation Models (DEM) incorporating…
Catastrophic transitions, where a system shifts abruptly between alternate steady states, are a generic feature of many nonlinear systems. Recently these regime shift were suggested as the mechanism underlies many ecological catastrophes,…
We propose a dynamical model for the estimation of Operational Risk in banking institutions. Operational Risk is the risk that a financial loss occurs as the result of failed processes. Examples of operational losses are the ones generated…
Geomechanical monitoring of a rock massif is an actively developing branch of geomechanics. It is almost impossible to single out a methodology and approaches for data collection and analysis in developing seismic monitoring systems. In the…
Current methods of estimating the change in stress caused by injecting fluid into subsurface formations require choosing the type of constitutive model and the model parameters based on core, log, and geophysical data during the…
We present a methodology for quantifying seismic velocity and pore pressure uncertainty that incorporates information regarding the geological history of a basin, rock physics, well log, drilling and seismic data. In particular, our…
A key part of planning CO2 storage sites is to devise a monitoring strategy. The aim of this strategy is to fulfill the requirements of legislations and lower cost of the operation by avoiding operational problems. If CCS is going to be a…
Sequential change point detection for multivariate autocorrelated data is a very common problem in practice. However, when the sensing resources are limited, only a subset of variables from the multivariate system can be observed at each…
Understanding the similarities and differences of the long term impact of different carbon dioxide removal (CDR) techniques is essential in determining the most effective and sustainable strategies to mitigate climate change. In particular,…
Natural gas hydrates are considered a potential resource for gas production on industrial scales. Gas hydrates contribute to the strength and stiffness of the hydrate-bearing sediments. During gas production, the geomechanical stability of…
Sea-levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and…
Detecting changes in asset co-movements is of much importance to financial practitioners, with numerous risk management benefits arising from the timely detection of breakdowns in historical correlations. In this article, we propose a…
In this paper, we introduce a probabilistic approach to risk assessment of robot systems by focusing on the impact of uncertainties. While various approaches to identifying systematic hazards (e.g., bugs, design flaws, etc.) can be found in…
We develop an averaging approach to robust risk measurement under payoff uncertainty. Instead of taking a worst-case value over an uncertainty neighborhood, we weight nearby payoffs more heavily under a chosen metric and average the…
Estimates of greenhouse gas emissions from Arctic estuarine environments are dominated by in situ summer-time ice-free dissolved gas measurements due to the logistical ease of performing field observations in these conditions. Recent…
Estimating density ratios between pairs of intractable data distributions is a core problem in probabilistic modeling, enabling principled comparisons of sample likelihoods under different data-generating processes across conditions and…
The maturity of structural health monitoring technology brings ever-increasing opportunities for geotechnical structures and underground infrastructure systems to track the risk of structural failure, such as settlement-induced building…
This study presents Part II of an AI-enhanced Decision Support System (DSS), extending Rahimi (2025, Part I) by introducing a fully uncertainty-aware optimization framework for long-term open-pit mine planning. Geological uncertainty is…