I'm a Computer Science undergraduate specializing in AI/ML at Misr International University, Cairo. Currently working as an AI/ML Engineering Intern at Ollimi AI and Programming Instructor at Preply, passionate about leveraging AI to solve real-world problems.

• 🔭 Currently working on Text-to-Speech models for Egyptian dialect at Ollimi AI
• 🎓 Teaching AI/ML fundamentals, NLP, and deep learning to 50+ students on Preply
• 🌱 Specializing in RAG systems, LLM fine-tuning, and vector databases
• 👯 Open to collaborate on AI/ML projects and open-source contributions
• 📫 Reach me at: aliabdalla2110@gmail.com | +201015929862
• 🌍 Based in Cairo, Egypt 🇪🇬

• Contributed to Text-to-Speech model training for Egyptian dialect, improving accent accuracy by 25%
• Implemented LoRA fine-tuning techniques on competing models, reducing inference time by 30%
• Optimized training pipelines for customer support and sales applications

• Teaching AI/ML fundamentals, NLP, and deep learning to 50+ students
• Specializing in Python, TensorFlow, scikit-learn, and transformer architectures
• Achieved 90% student completion rate with comprehensive LLM and RAG system instruction
• Led 10+ successful student capstone projects

Intelligent multi-agent meal planning system using CrewAI framework

• Tech Stack: Python, CrewAI, OpenAI API, LangChain, Multi-agent systems
• Features: AI-powered recipe research, budget analysis, shopping list organization, leftover management
• Impact: Comprehensive meal planning solution with dietary restriction support

RAG-powered CLI application with semantic search capabilities

• Tech Stack: Python, ChromaDB, OpenAI embeddings, RAG architecture
• Features: Semantic search, advanced filtering, conversational AI chatbot
• Achievement: 85% recommendation accuracy with semantic search

End-to-end ML pipeline for real estate price prediction

• Tech Stack: Python, XGBoost, Node.js, EJS, feature engineering
• Features: 92% accuracy prediction, full-stack deployment, 1000+ data points
• Impact: Complete web application with advanced ML algorithms

Interactive RAG-based conversational AI with modern UI

• Tech Stack: Python, Gradio, RAG architecture, LangChain
• Features: Real-time chat, semantic retrieval, response generation pipeline
• Achievement: 40% improvement in conversation engagement

Scalable employee management system with vector-based semantic search

• Tech Stack: ChromaDB, embeddings, vector search, access control
• Features: 50% query performance optimization, 1000+ employee records
• Impact: Role-based access control with efficient indexing strategies

Misr International University, Cairo, Egypt 2022-2026

• LangChain & LangGraph Advanced RAG Applications - Coursera
• Advanced LangChain, LLMOps & Retrieval-Augmented Generation - Coursera
• Machine Learning A-Z - Udemy

🏆 Alternative Trophy View

class AliAbdallah:
    def __init__(self):
        self.name = "Ali Abdallah"
        self.role = "AI/ML Student & Engineer"
        self.location = "Cairo, Egypt"
        
    def current_work(self):
        return [
            "AI/ML Engineering Intern @ Ollimi AI",
            "Programming Instructor @ Preply",
            "Advanced RAG Systems Development",
            "LLM Fine-tuning & Model Optimization"
        ]
    
    def skills(self):
        return {
            "AI/ML": ["Deep Learning", "NLP", "Computer Vision", "LLM Fine-tuning"],
            "Frameworks": ["TensorFlow", "PyTorch", "LangChain", "Hugging Face"],
            "Databases": ["ChromaDB", "FAISS", "PostgreSQL", "MongoDB"],
            "Languages": ["Python", "JavaScript", "C++", "Java"]
        }
    
    def goals_2025(self):
        return [
            "Master advanced RAG architectures",
            "Contribute to open-source AI projects",
            "Complete AI/ML specialization degree",
            "Build production-ready ML applications"
        ]

"No one knows your capabilites but Yourself."