Abed Hammoud
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  • Under Review
    • Reinforcement Learning, Optimal Control, and Bayesian Filtering in Data Assimilation
    • Train Long, Think Short: Curriculum Learning for Efficient Reasoning
  • News & Talks
    • Speaking at AGU Fall Meeting 2025 — Developments in ML across Earth-System Modeling
    • Awarded the Gordon and Betty Moore Foundation Postdoctoral Fellowship!
    • Convening a session at AGU 2025
    • Abstract accepted to AMS BLT '25!
    • Presented at the Princeton Fluids Seminar!
    • I was awarded with the KAUST PSE dean's award! (First to achieve the highest number of awards possible within a PhD)
    • NCAR Exploratory Computing Allocation awarded (UPRI0030)
    • Invited talk at the RWTH-Aachen Uncertainty Quantification Seminar
    • Started my postdoc at Princeton University
    • Selected as a Princeton–NOAA GFDL CIMES Fellow
    • Invited to give a talk at AUB CAMS!
    • Invited to give a talk at the Stochastic Numerics and Stochastic Learning Conference!
    • Defended my PhD at KAUST!
    • I was awarded with the KAUST PSE dean's award for 2024!
    • Invited to give a talk at ISDA online!
    • Attended SIAM UQ '24 in Trieste!
    • Visited Prof. Dionysios Raitsos at Univ. of Athens!
    • Accepted to the Les Houches Summer School for 200 Years of Navier Stokes and Turbulences!
    • Gave a Talk at the Ocean Colloquium!
    • I was awarded with the inaugural KAUST PSE dean's award!
    • Gave a Talk at ISDA 2022!
    • Participated in the TU Delft DCSE Fall School on ROMs and UQ!
  • Publications
    • From Standard to Bayesian: Revisiting Ocean Color Model Evaluation
    • The new Climate Change Center of Saudi Arabia — A big step towards understanding and predicting the distinct climate of the Arabian Peninsula
    • On the potential of Bayesian neural networks for estimating chlorophyll-a concentration from satellite data
    • Identification of Moving Sources in Stochastic Fields: A Bayesian Inferential Approach with Application to Marine Traffic in the Mediterranean Sea
    • Downscaling Using CDAnet Under Observational and Model Noises: The Rayleigh-Bénard Convection Paradigm
    • Data Assimilation in Chaotic Systems Using Deep Reinforcement Learning
    • Two-step AI-aided Bayesian source identification of urban-scale pollution
    • Oil spill risk analysis for the NEOM shoreline
    • Global Sensitivity Analysis of an Oil Spill Model: a Regularized Regression Approach.
    • Semantic Segmentation of Mesoscale Eddies in the Arabian Sea: A Deep Learning Approach
    • CDAnet: A Physics-Informed Deep Neural Network for Downscaling Fluid Flows
    • A Physics-Informed Deep Neural Network for Backward in Time Prediction: Application to Rayleigh-Bénard Convection
    • Continuous and discrete data assimilation with noisy observations for the Rayleigh-Bénard convection: a computational study
    • Moving source identification in an uncertain marine flow: Mediterranean Sea application
    • Towards an End-to-End Analysis and Prediction System for Weather, Climate, and Marine Applications in the Red Sea
  • Publication_feats
    • Data Assimilation in Chaotic Systems Using Deep Reinforcement Learning
    • CDAnet: A Physics-Informed Deep Neural Network for Downscaling Fluid Flows
    • A Physics-Informed Deep Neural Network for Backward in Time Prediction: Application to Rayleigh-Bénard Convection
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  • Projects
    • Pandas
    • PyTorch
    • scikit-learn
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  • Teaching
    • Learn JavaScript
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  • Recent & Upcoming Talks

Speaking at AGU Fall Meeting 2025 — Developments in ML across Earth-System Modeling

Dec 15, 2025 · 1 min read

Presenting recent work on data-driven flux parameterization in the atmospheric boundary layer.

Last updated on Dec 15, 2025
Abed Hammoud
Authors
Abed Hammoud
Postdoctoral Research Associate
Awarded the Gordon and Betty Moore Foundation Postdoctoral Fellowship! Dec 1, 2025 →

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