I am a data-driven tech professional with a strong background in Computer Science. My core expertise lies in utilizing Power BI, SQL, and Python to analyze data, build smart systems, and develop AI-driven solutions. I enjoy tackling real-world problems through logical problem-solving and interactive data visualizations. This portfolio highlights my practical work in data analytics and artificial intelligence.

Recent Work

Data-Driven Sales Strategy Optimization

Analyzed product sales data to evaluate the performance of different outreach methods. Utilized Python (Pandas, Seaborn) for data cleaning, EDA, and defining a custom 'Sales Efficiency' metric. Delivered actionable business recommendations to maximize revenue while minimizing team time costs.

Arabic Handwritten Character Similarity Search using EfficientNet

An image-based search tool for handwritten Arabic characters, built with PyTorch. It uses EfficientNet B3 to extract deep features and cosine similarity to find the top 5 most visually similar characters from a custom dataset. The project includes preprocessing, feature extraction, and result visualization.

Bone Fracture Classification Using Transfer Learning with EfficientNetV2

Fine-tuned EfficientNetV2-M for bone fracture classification using X-ray images across 12 classes. Built with PyTorch, the project includes data loading, training/validation loops, and transfer learning for accurate medical image classification.

Exploring NYC Public School SAT Performance with Pandas

Analyzed NYC SAT scores using pandas to identify top schools, overall rankings, and borough-wise score variability.

Web scraping GameStop (GME) Stock & Revenue Analysis with Python

This project explores GameStop Corp. (GME) using both historical stock price data from Yahoo Finance and revenue data scraped from the web.