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MhmdEsml/README.md

💫 About Me:

I am a passionate researcher working on the application of 3D deep learning models for digital rock physics. Currently, I am exploring advanced neural network architectures to simulate and analyze porous media, with a focus on leveraging JAX and Flax or PyTorch for scalable, efficient model training. I am open to collaboration and discussions on these topics—feel free to reach out if you're interested in contributing to this exciting field!

🌐 Socials:

LinkedIn email

💻 Tech Stack:

Python JAX Flax PyTorch TensorFlow Keras Matplotlib NumPy Pandas Plotly scikit-learn SciPy Fortran C++ R MySQL

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  1. DDPM-Digital-Rock-Analysis DDPM-Digital-Rock-Analysis Public

    Generating synthetic carbonate and sandstone CT scan images by Denoising Diffusion Probabilistic Models

    Python 8 3

  2. Segmentation-Digital-Rock-Images Segmentation-Digital-Rock-Images Public

    Performing semantic segmentation on 11 dataset from the Digital Rock Portal

    Python 3

  3. Two-Point-Correlation-GPU-TPU Two-Point-Correlation-GPU-TPU Public

    TPC is a specialized Python library for accelerated computation of Two-Point Correlation Functions (TPC) in 3D porous materials and microstructures. It provides significant performance improvements…

    Jupyter Notebook

  4. The-Duke-University-Cervical-Spine-MRI-Segmentation The-Duke-University-Cervical-Spine-MRI-Segmentation Public

    A comprehensive 3D medical image segmentation pipeline for cervical spine MRI using an enhanced 3D U-Net architecture.

    Python

  5. 3d-porous-media-gan 3d-porous-media-gan Public

    A 3D Conditional Generative Adversarial Network (GAN) for synthesizing realistic porous media microstructures with precise porosity control. Built with JAX/Flax for TPU/GPU-accelerated training and…

    Python 2