conference-abstract

Flash floods, driven by short-duration, high-intensity rainfall, are among the most destructive hydrometeorological hazards in West …

The combined effect of population growth, urbanization, and intensification of extremes due to climate change is expected to increase …

Flash floods are one of the deadliest types of floods due to their rapid onset and space-time characteristics. Early detection and …

In this work we investigate the transferability/applicability of ML-based flood prediction models trained in data rich regions for flood prediction in ungauged regions in the UK, Brazil, Chile and Australia. Our results suggest great promise of using such models with NASA IMERG precipitation observations.

In this work we are showcasing an initial assessment on the viability of downscaling (upsampling) low-resolution flood inundation maps to finer spatial resolution via a multi-layer Residual Deep Network that leverages relevant topographic data.

Machine learning (ML) based models have demonstrated a great potential for streamflow prediction. ML based procedures are relatively …

In this work we share some of our preliminary findings about predicting the timing of software vulnerability exploitations based on the vulnerabilities’ social media popularity.

In this paper we lay out the design of a social network analysis framework, developed under DARPA’s SocialSim program. Our novel architecture models human emotional, cognitive and other social factors. Furthermore, we showcase results of modeling cryptocurrencies, cyber threats, and software vulnerabilities for three interrelated social environments, namely GitHub, Reddit, and Twitter.