Welcome to my Portfolio
I’m an AI and Full-Stack Engineer focused on building intelligent systems using machine learning and deep learning. I specialize in developing end-to-end AI solutions, from data preprocessing to model optimization and deployment, and I’m passionate about solving real-world problems with data-driven approaches.
Contact & Profiles
Featured Projects
Deep_Audio_Classifier_using_CNN
Audio classification with Mel-spectrogram CNNs.
Animal_Image_Classification_Using_InceptionV3
InceptionV3-based animal image classifier with data cleaning
Brain_Tumor_Classification_with_InceptionV3-Grad-CAM
InceptionV3-based brain tumor detection with Grad-CAM.
CNN_Autoencoder_For_Image_Denoising
U-Net based CNN autoencoder designed to denoise noisy image.
Inceptionv3_Dog_VS_Cat_Classifier
Cat vs Dog classifier with InceptionV3 model.
High-Accuracy-Cats-vs-Dogs-InceptionV3
In this notebook, I build a high-accuracy Cat vs. Dog classifier using InceptionV3 and transfer learning. After thorough EDA and robust tf.data preprocessing, the model achieves ~99% test accuracy with strong generalization and no overfitting.
Brain-Tumor-Classification-with-Grad-CAM
A deep learning pipeline for classifying brain tumor MRI images using InceptionV3 and Grad-CAM. Includes full preprocessing, augmentation, tf.data pipelines, transfer learning, evaluation metrics, and interpretable heatmaps for reliable medical image analysis.
Audio-Classification-Raw-Audio-to-Mel-Spectrogram-CNNs
Complete end-to-end audio classification pipeline using deep learning. From raw recordings to Mel spectrogram CNNs, includes preprocessing, augmentation, dataset validation, model training, and evaluation, a reproducible blueprint for speech, environmental, or general sound classification tasks.
Animal-Image-Classification-Using-InceptionV3
This project builds an animal image classification system using TensorFlow and InceptionV3. It includes a full data-cleaning pipeline that detects corrupted images, duplicates, brightness issues, and mislabeled samples before training a transfer-learning model for accurate and reliable predictions.
CNN_Autoencoder_For_Image_Denoising
A U-Net based CNN autoencoder designed to denoise noisy images before classification, improving input quality and boosting overall model accuracy.
Experience
AI Engineer (Personal Projects)
Self-Employed / Independent Projects
Ajman, UAE
Jan 2022 - Present
Designed and implemented multiple AI and Machine Learning projects to strengthen practical understanding of ML, Deep Learning, and data-driven problem solving.
- ✓Built and trained ML models from scratch
- ✓Implemented Neural Networks including Perceptron and XOR Machine Learning projects
- ✓Developed data preprocessing and feature engineering pipelines
- ✓Applied model evaluation techniques (ROC, AUC, R², Cross-Validation)
- ✓Integrated projects with databases (Supabase)
Smart Classroom – Graduation Project
Arab Academy for Science, Technology & Maritime Transport (AASTMT)
Alexandria, Egypt
Oct 2023 - Feb 2024
Designed and developed an intelligent smart classroom system integrating AI, IoT, and embedded systems for real-time environment monitoring and automated device control.
- ✓Implemented YOLO-based object detection for classroom monitoring
- ✓Deployed solution on Raspberry Pi using edge computing
- ✓Automated lights, AC, projectors, and curtains using motion and temperature sensors
- ✓Developed a Flutter mobile application for remote control and monitoring
- ✓Integrated AI models with IoT hardware for real-time intelligent decision-making
Certifications
Bachelor of Science in Computer Science
Arab Academy for Science, Technology & Maritime Transport (AASTMT)
Studied core Computer Science subjects including programming, data structures, algorithms, databases, artificial intelligence, and software engineering. Gained strong analytical and problem-solving skills through academic coursework and practical projects.
February 20, 2024
AI Trainer
Digital Hub
Completed digital transformation training program Track: Artificial Intelligence, Associate Level based IBM.
January 1, 2023
IoT Trainer
Digital Hub
Completed digital transformation training program Track: IoT, Associate Level based IBM.
January 1, 2023
Cisco Networking Academy Certificates
CISCO
Cisco Networking Academy Certificates – Networking Fundamentals, Routing & Switching, IT Essentials.
January 1, 2022
View Certificate →Soft Skills
HRDC (Cairo)
Certified in Soft Skills, including communication, teamwork, and problem-solving.
August 31, 2021
Hult Prize Regional Finals Competitor
Cairo Impact Summit
As a Competitor in the Regional Finals, hosted at the 2021 Cairo Impact Summit.
April 1, 2021
Published Articles
Building a Near-Perfect Cat vs. Dog Classifier with InceptionV3
High-accuracy InceptionV3 pipeline for cat vs. dog image classification with robust preprocessing.
Brain Tumor Classification Using InceptionV3 and Grad-CAM: A Deep Learning Pipeline
End-to-end deep learning pipeline using InceptionV3 and Grad-CAM for accurate and interpretable brain tumor MRI classification.
Building a Complete Audio Classification Pipeline Using Deep Learning: From Raw Audio to Mel Spectrogram CNNs
Built an end-to-end audio classification pipeline using CNNs on Mel spectrograms, with data cleaning, augmentation, and deep learning for reliable multi-class predictions.
Building a Clean, Reliable, and Accurate Animal Classifier Using InceptionV3
Built an animal image classification pipeline using TensorFlow and InceptionV3, focusing on thorough data cleaning, preprocessing, and transfer learning for accurate results.
A U-Net–Based CNN Autoencoder for Cleaning Noisy Images Before Classification
A practical walkthrough of how I built and trained a deep-learning model to denoise images and boost classification performance.
Interested in collaborating?
I'm always open to new opportunities and interesting projects. Feel free to reach out!
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