Postdoc, Princeton University, New Jersey, USA/ ALUMNI PhD Student
Alumni
Social Profile:
Abed is interested in interdisciplinary research involving innovative integration of artificial intelligence methodologies, with particular emphasis on deep reinforcement learning, scientific computing and uncertainty quantification.
During his studies, he applied computational techniques to a broad spectrum of problems in fluid mechanics, environmental flows, pollution assessment and remote sensing.
By leveraging the capabilities of artificial intelligence, he aims to develop predictive models that extract the most value out of incoming data, while also accounting for inherent uncertainties in the model parameters and data.
Hammoud, M.A.E.R., Titi, E.S., Hoteit, I., & Knio, O. (2022). CDAnet: A Physics‐Informed Deep Neural Network for Downscaling Fluid Flows. Journal of Advances in Modeling Earth Systems
Hammoud, M.A.E.R., Le Maître, O., Titi, E. S., Hoteit, I., & Knio, O. (2023). Continuous and discrete data assimilation with noisy observations for the Rayleigh-Bénard convection: a computational study. Computational Geosciences
Hammoud, M.A.E.R., Alwassel, H., Ghanem, B., Knio, O., & Hoteit, I. (2023). Physics-Informed Deep Neural Network for Backward-in-Time Prediction: Application to Rayleigh–Bénard Convection. Artificial Intelligence for the Earth Systems
"KAUST shall be a beacon for peace, hope and reconciliation, and shall serve the people of the Kingdom and the world."
King Abdullah bin Abdulaziz Al Saud, 1924 – 2015
Thuwal 23955-6900, Kingdom of Saudi Arabia
Al-Khwarizmi Building (1)
© King Abdullah University of Science and Technology. All rights reserved