Hossam Elghati

Developed a scalable data pipeline for processing and analyzing large volumes of influencer content, integrating advanced data engineering techniques and a machine learning model to predict and enhance content virality. Applied NLP techniques for actionable content recommendations. Built a CNN model for early breast cancer detection from histopathology images, enhancing medical diagnostics. Created an OCR system with Tesseract for extracting blood analysis results with improved accuracy and reliability. Managed data from multiple sources for consistent product click-through rate prediction using machine learning models. Developed and fine-tuned the Llama2 model on medical datasets to build an AI-powered virtual assistant supporting efficient online consultations and patient care.

Developed a scalable data pipeline for processing and analyzing large volumes of influencer content, integrating advanced data engineering techniques with machine learning to predict and enhance content virality. Applied NLP techniques to generate actionable content recommendations. Collected, merged, and transformed data from multiple sources to ensure consistency for product click-through rate prediction. Trained machine learning models to derive insights and support data-driven decision-making. Developed and fine-tuned the Llama2 model on medical datasets to create an AI-powered virtual assistant capable of answering patient queries, significantly improving online consultation efficiency and patient care through accurate and timely responses.

Developed semantic segmentation models using DeepLabV3+ to detect and segment rust in images for industrial inspection, enabling early detection and maintenance planning. Built an instance segmentation model YOLOv11 for crack detection producing precise masks for automated damage assessment in civil and structural engineering applications. Implemented integration of trained machine learning models into a Python backend application with an ABP Framework frontend, enhancing seamless model consumption. Contributed to MLOps pipeline design, managing post-prediction correction, annotation conversion, and model retraining to improve accuracy with continuous learning. Performed maintenance and feature enhancements on an ABP Framework project, working on both .NET backend and Angular frontend, improving performance, fixing bugs, and extending functionality.