プロフィール詳細

プロジェクトを作成

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Dr. Omar S.に依頼

United States

Specialist in High-Performance Computing, CFD, and Generative AI for Engineering and Environmental Systems

プロフィール概要

I am a researcher and engineer specializing in computational fluid dynamics (CFD), hydrodynamic flood modeling, and generative machine learning for fluid mechanics and environmental applications. My work integrates high-performance computing with advanced AI methods to tackle challenges in climate resilience, renewable energy, and marine/offshore engineering. I have developed and applied diffusion models, GANs, and physics-informed neural networks for tasks such as flood forecasting, atmospheric boundary layer and hurricane inflow super-resolution, turbulent inflow generation, and sub-grid scale modeling of large eddy simulations. My contributions include designing latent space compression tools such as variational autoencoders and neural implicit flow networks, enabling efficient training of diffusion models and data-driven turbulence modeling. In addition to AI research, I bring strong expertise in high-fidelity CFD of offshore structures, free-surface flows, and wave–structure interactions using OpenFOAM and in-house solvers. I have conducted extensive work on wave energy converters, floating structures, and two-phase turbulence. My background also covers experimental methods, including stereo vision ocean monitoring, in-lab wave tank testing, buoy data analysis, and motion tracking for vessels and high-speed craft. Complementing these, I have experience in data acquisition (DAQ) system design, developing hardware/software for GNSS, IMU, and vision-based motion tracking in naval and offshore projects. I have also created FEM solvers for coupled thermo-fluids problems. Overall, my expertise lies at the intersection of fluid mechanics, numerical simulation, and generative AI—developing computational and experimental frameworks that bridge physics, machine learning, and engineering applications for real-world impact.

専門分野

• ☆ Engineering Education
• ☆ Computer Science
• ☆ Supercomputing
• ☆ Computer-Aided Engineering
• ☆ Engineering Thermodynamics/Thermophysical Engineering
• ☆ Ocean Engineering
• ☆ Remote Sensing
• ☆ Heat Transfer & Calorimetry
• ☆ Fluid Mechanics
• ☆ Computational Fluid Dynamics
• ☆ Environmental Engineering and Technology
• ☆ Applied Mathematics
• ☆ Mathematical Models
• ☆ Computational Sciences
• ☆ Differential Equations
• ☆ Marine Engineering
• ☆ Engineering Design
• ☆ Python

サービス

• Writing
• Research
• Consulting
• Data & AI
• Product Development

Writing General Proofreading & Editing

Research Technology Scouting, Fact Checking, Systematic Literature Review

Consulting Manufacturing Consulting

Data & AI Predictive Modeling, Statistical Analysis, Image Processing, Image Analysis, Algorithm Design-Non ML, Algorithm Design-ML, Data Visualization, Big Data Analytics, Data Processing, Data Insights

Product Development Product Evaluation, Product Validation, Prototyping, Reverse Engineering, Device Fabrication

職務経験

Postdoctorate

Argonne National Lab

6月 2025 - 現在

Graduate Research Assistant / Research Assistant

Texas A&M University

8月 2020 - 8月 2025

学歴

Doctorate

Texas A&M University - College Station - United States

8月 2019 - 8月 2025

認定資格

• 認定資格の詳細は未入力です。

出版物

JOURNAL ARTICLE

Omar Sallam, Mirjam Fürth (2025). Dual scale Residual-Network for turbulent flow sub grid scale resolving: A prior analysis . Computers & Fluids.

Omar Sallam, Rihui Feng, Jack Stason, Xinguo Wang, Mirjam Fürth (2024). Stereo vision based systems for sea-state measurement and floating structures monitoring . Signal Processing: Image Communication.

Omar Sallam, Mirjam Fürth (2023). On the use of Fourier Features-Physics Informed Neural Networks (FF-PINN) for forward and inverse fluid mechanics problems . Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment.

Omar Sallam, Yijun Sun, Ahmed A Hamada, Björn Windén, Mirjam Fürth (2023). The application of laminar numerical wave tank for a heaving buoy hydrodynamics study in low-turbulence nonlinear waves . Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment.

Omar Sallam, Jane-Frances Igbadumhe, Jack Bonoli, John Dzielski, Mirjam Fürth (2022). Equivalent linear roll damping of a FPSO coupled with liquid sloshing in a pair of two-row tanks . Ocean Engineering.