Featured Projects

Data Science, Machine Learning & Scientific Computing

Explore my work in research, visualization, and AI applications

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Micro-fossil Classification

Organization: KAUST Visualization Lab | Period: 2025 - 2026

Led a team of KAUST staff to develop an advanced deep learning system for micro-fossil classification from 2D Micro-CT slices. Managed data provenance and coordinated analysis workflows to achieve high-accuracy species identification.

Deep Learning PyTorch Micro-CT Imaging Team Leadership

Impact: Enabled automated foraminifera species classification with unprecedented accuracy

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Coral Health Assessment

Organization: KAUST Visualization Lab | Period: 2023 - 2025

Developed an AI-powered coral health assessment application using Meta's Segment Anything Model (SAM) to analyze underwater coral photographs. Created containerized solutions and built a user-friendly application for marine scientists to assess coral health indicators.

Computer Vision SAM (Meta AI) Docker Python Marine Biology

Impact: Published tool (Coral-CAT) enabling semi-automatic coral color analysis for researchers

SlideGAN Optimization

Organization: KAUST Visualization Lab | Period: 2023 - 2025

Led engineering team to refactor and optimize SlideGAN code for 3D seismic microstructure generation. Conducted comprehensive strong scalability testing across multiple GPU configurations to maximize performance.

GANs GPU Optimization HPC Code Refactoring Performance Testing

Impact: Achieved significant performance improvements enabling faster seismic data generation

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AI for Protein-Protein Interaction Prediction

Organization: KAUST AI Initiative | Period: 2019 - 2023 | Funding: USD $112,000

Secured major funding from KAUST AI Initiative to develop innovative AI strategies for protein-protein interaction prediction at the structural level. Implemented weakly supervised data augmentation and created three enhanced machine learning classifiers. Produced three peer-reviewed publications.

Machine Learning Structural Biology Data Augmentation Protein Docking Bioinformatics

Impact: Advanced protein interaction prediction accuracy, resulting in 3 scientific publications

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Shaheen III Supercomputer Performance Testing

Organization: KAUST RCCL | Period: 2022 - 2023

Developed comprehensive benchmark suite for Shaheen III supercomputer performance evaluation. Created Python-based HPC applications to identify performance bottlenecks and optimize system efficiency for production workloads.

HPC Python Benchmarking Performance Analysis Supercomputing

Impact: Validated performance capabilities of Shaheen III before production deployment

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