2 citations · 2 across the 3 of their papers we have counts for
4 papers
A Model-Agnostic Physics-Guided Adapter for Few-Shot Transfer of Coastal Flood Prediction Models to Unseen Regions
Bilal Hassan, Areg Karapetyan, Samer Madanat
Deep learning surrogates can produce high-resolution coastal flood maps orders of magnitude faster than physics-based hydrodynamic simulators, yet transferring them to new coastal…
UniST-Pred: A Robust Unified Framework for Spatio-Temporal Traffic Forecasting in Transportation Networks Under Disruptions
Yue Wang, Areg Karapetyan, Djellel Difallah +1
Spatio-temporal traffic forecasting is a core component of intelligent transportation systems, supporting various downstream tasks such as signal control and network-level traffic…
Climate Adaptation-Aware Flood Prediction for Coastal Cities Using Deep Learning
Bilal Hassan, Areg Karapetyan, Aaron Chung Hin Chow +1
Climate change and sea-level rise (SLR) pose escalating threats to coastal cities, intensifying the need for efficient and accurate methods to predict potential flood hazards. Trad…
Deep Vision-Based Framework for Coastal Flood Prediction Under Climate Change Impacts and Shoreline Adaptations
Areg Karapetyan, Aaron Chung Hin Chow, Samer Madanat
In light of growing threats posed by climate change in general and sea level rise (SLR) in particular, the necessity for computationally efficient means to estimate and analyze pot…