Lian Abushaikha

As a motivated computational and data science undergraduate student at George Mason University specializing in machine learning, I bring advanced programming skills in Python, C/C++, Java, Julia, Jupyter Notebook, and SQL. With a solid foundation in data structures and complex problem-solving, I am eager to kickstart my career in software development and machine learning through an internship. My goal is to contribute to real-world projects, enhance my development skills, and launch my professional career.

• Database Architecture and Advanced Data Analytics: Architected and deployed a robust MySQL database system derived from real-world data. Crafted a comprehensive ER model and engineered a normalized relational schema. Executed complex data analysis through advanced SQL queries, culminating in a comprehensive report that integrated detailed diagrams and in-depth analysis, reflecting a high level of expertise in database architecture and SQL analytics.
• SQL to Julia Language Transition: Engineered the seamless translation of a comprehensive data analysis workflow from SQL to Julia as part of a capstone project. Conducted in-depth research and applied sophisticated methodologies for converting intricate SQL queries into efficient Julia code, showcasing advanced proficiency in both SQL and Julia, and demonstrating adaptability in leveraging multiple programming languages for data analysis.
• Wrapped KD-Tree Implementation in Java: Engineered and optimized a sophisticated variant of the kd-tree data structure, known as a wrapped kd-tree, in Java. This advanced data structure efficiently stores and manages large datasets of points in 2-dimensional space, supporting dynamic operations such as insertion, deletion, and a variety of complex geometric queries, reflecting deep expertise in spatial algorithms and Java programming.
• Advanced Image Classification in Python: Utilized Python to implement the Bag of Features algorithm, creating a high-precision image classification system focused on feature extraction and pattern recognition. This solution effectively categorized images based on distinct visual attributes, showcasing advanced proficiency in machine learning, computer vision, and algorithmic development in Python.