Yousef Emad

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Credit Card Fraud Detection Using Machine Learning & Deep Learning=>Link

Mar 2025 - Apr 2025 (2 months)

• Designed an anomaly detection pipeline using OC-NN, Isolation Forest, LOF, Autoencoder, and Deep SVDD, achieving 99.65% accuracy on 1.3M transactions. • Optimized fraud detection by fine-tuning models, reducing false positives, and enhancing precision-recall trade-offs for real-world financial impact.

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Forum Discussion Categorization Using NLP& Deep Learning=>Link

Mar 2025 - Apr 2025 (2 months)

• Ranked 1st in a university-hosted Kaggle competition (200+ participants) by building an NLP-driven model to classify discussions into 5 categories using GRU & BERT. • Optimized performance with hyperparameter tuning, data augmentation, and ensemble learning, significantly outperforming baseline models.

S

Smart Accident & Emergency Response System Using Deep Learning =>Link

Jan 2025 - Current (1 year 6 months)

• Fine-tuned YOLOv8 for real-time accident and injury detection; implemented Mask R-CNN for blood loss segmentation. Used transfer learning with MobileNetV2 to classify age groups and gender of injured individuals. Built a first-aid Q&A chatbot using Retrieval-Augmented Generation (RAG) with LLM APIs to deliver accurate medical guidance.

S

Sentiment Analysis Using NLP& Deep Learning

Jan 2025 - Apr 2025 (4 months)

• Processed 1.6 million tweets for sentiment classification using NLP techniques and data preprocessing. • Implemented RNN, CNN-LSTM, BiLSTM, Stacked GRU, BiGRU, and Transformer models for text classification. • Achieved high accuracy by optimizing model architecture, using embedding layers, bidirectional networks, and attention mechanisms. z

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Semantic Segmentation of Street Scenes Using Deep Learning

Jan 2025 - Mar 2025 (3 months)

=>Link • Developed a U-Net-based segmentation model with data augmentation & class imbalance handling for improved accuracy. • Achieved high IoU, Dice Coefficient, Precision & Recall on a multi-class dataset, enhancing model performance.

A

Apartment Rent Prediction Using Python & Machine Learning=>Link

May 2023 - Sep 2023 (5 months)

• Built ML models for both regression & classification to predict rent prices, leveraging extensive data analysis & feature engineering. • Engineered key features (price extraction, encoding, geographic variables) & handled outliers, optimizing interpretability (MAE, MSE, RMSE, R²).

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