Abed Hammoud

Abed Hammoud, Ph.D., is a Postdoctoral Researcher at Princeton University working in the TUNE lab on subgrid-scale parametrization of land-surface interactions for heterogeneous surfaces with Arctic pole specialization.

His academic credentials include:

• Ph.D. in Mechanical Engineering, 2024, King Abdullah University of Science and Technology
• MSc in Mechanical Engineering, 2020, King Abdullah University of Science and Technology
• BEng in Mechanical Engineering, 2020, American University of Beirut

Research spans artificial intelligence, applied mathematics, and environmental fluid mechanics with core focus on deep learning-enhanced data assimilation, downscaling, and state estimation. Additional expertise covers uncertainty quantification, reduced order models, and sensitivity analysis applied to marine pollution tracking and oceanic remote sensing systems.

Publication analysis (2021-2024) reveals concentrated innovation in physics-informed neural networks for fluid dynamics prediction, chaotic system data assimilation, and computational convection modeling—demonstrating consistent integration of deep reinforcement learning with earth system science challenges.

As a TUNE lab member, he contributes to collaborative projects advancing AI-driven environmental fluid mechanics and land-surface interaction modeling.