🧑‍💻 AI Engineering Intern @ Bio-Techne.
🎓 Master's Student in Artificial Intelligence.
💻 Machine Learning & Generative AI Developer.
📊 Passionate about data-driven insights, intelligent systems, and cloud AI technologies.

I am currently pursuing a Master’s Degree in Artificial Intelligence at the University of St. Thomas (UST).
My interests include machine learning, deep learning, generative AI, and data science, with experience building models, dashboards, and end-to-end ML pipelines.

I enjoy transforming data into insights and developing intelligent systems using modern AI tools and cloud platforms.

Master’s Degree – Artificial Intelligence
University of St. Thomas (UST) (Current)

Bachelor’s Degree – Computer Science
Misr International University (MIU), 2021

High School
El Gouna International School (EGIS), 2017

• Python
• Java
• C++
• JavaScript
• Streamlit

• NumPy
• Pandas
• Scikit-Learn
• Feature Engineering
• Model Evaluation & Optimization
• Retrieval-Augmented Generation (RAG)

• CNNs
• YOLO
• ResNet
• TensorFlow
• Keras
• Sentence-Transformers (Cross-Encoders)
• OCR (PaddleOCR)

• Matplotlib
• Seaborn
• Tableau
• Power BI

• LLM Fundamentals
• Image Generation
• Prompt Engineering (Vertex AI, AWS)
• Responsible AI
• Prompt-Injection Safety

• AWS (ML & GenAI services)
• Google Cloud (Vertex AI, GenAI APIs)
• Azure (Solutions Architect Fundamentals)
• Databricks (SQL Warehouse, Vector Search, Model Serving, Unity Catalog, Asset Bundles)

• Git
• Linux
• Jupyter Notebook
• REST API Development
• Airflow
• MLflow
• OpenTelemetry
• Databricks CLI / Asset Bundles

Detection of Wild Oats based on Support Vector Machine Algorithms
MIUCC Conference for International Mobile Intelligent and Ubiquitous Computing (2021)

Wild Oats Dataset

• Built and published a custom dataset for wild oats detection on Kaggle.

Built a Databricks App (Streamlit) that ingests supplier/customer-care questionnaire and manual PDFs, extracts structured context, and retrieves AI-assisted answers from two Unity Catalog vector indexes (historical Questionnaires + Manuals & Guides) with cross-encoder re-ranking. Includes OCR (PP-OCRv6 MLflow models), prompt-injection safety, review/feedback workflow, PDF export, and OpenTelemetry telemetry. Built with:

• Python & Streamlit
• Databricks (SQL Warehouse, Vector Search, Model Serving, Unity Catalog)
• PyMuPDF & PaddleOCR
• Sentence-Transformers (cross-encoder re-ranking)
• OpenTelemetry
• MLflow (evaluation harness)

Built an end-to-end machine learning pipeline using the HSLS:09 dataset to predict GPA categories using:

• Feature selection
• Linear Discriminant Analysis (LDA)
• Ensemble learning models

Created a Power BI dashboard analyzing socioeconomic disparities and key trends.

Analyzed Zillow housing trends using Python (Pandas, NumPy, Seaborn) to generate investment insights.

Developed ML/DL models to classify wheat impurities using:

• Python
• Flask
• Laravel
• HTML/CSS
• JavaScript

Built a data analysis and visualization dashboard using Python and IBM Watson Studio.

Performed EDA and predictive modeling on housing data using Python and IBM Watson tools.

Data mining and visualization project analyzing contribution patterns using Python.

Explored cryptocurrency price movements, trends, and correlations using Python.

Analyzed content trends and popularity metrics using Python.

Explored Google Play Store datasets to identify market trends.

Statistical analysis and visualization of pandemic trends using Python.

• AWS Cloud Quest: Generative AI Practitioner
• Microsoft MCIT Scholarship – Azure Solutions Architect Expert
• AWS Machine Learning Scholarship – Udacity
• Data Scientist Program Scholarship – DataCamp
• IBM Data Science Professional Certificate – Coursera
• Fundamentals of Machine Learning and AI – AWS
• Introduction to Generative AI – Google Skills Boost
• Introduction to Large Language Models – Google
• Introduction to Image Generation – Google
• Responsible AI – Google
• Vertex AI Studio & Prompt Design – Google Cloud
• Deep Learning Fundamentals – IBM
• Deep Learning Essentials – IBM
• The Data Scientist’s Toolbox – Johns Hopkins University
• Agile Explorer – IBM SkillsBuild
• Python 3 Programming – Udemy
• Fundamentals of Visualization with Tableau – UC Davis
• Introduction to Tableau – 365 Data Science

• Advanced Generative AI systems
• LLM applications
• MLOps and scalable ML pipelines
• AI model deployment on cloud platforms

LinkedIn: [https://www.linkedin.com/in/abanoubgeorge/]

⭐ Always learning, building, and exploring new possibilities with AI.