I’m passionate about solving real-world problems through technology, whether that’s developing web applications, building AI models, or crafting efficient software solutions. Right now, I'm diving deep into AI/ML through the Break Through Tech AI program @ MIT, where I’m gaining hands-on experience with machine learning techniques, from data preprocessing, to model development, to evaluation and refinement.

I’m always looking for new ways to apply my skills in real-world projects and continue learning from others in the field. Got any exciting opportunities? Let’s connect!

Developed a full-stack Sudoku solver web application with support for manual, CSV, and image-based puzzle input

• Tech Stack: React, Tailwind, Flask, Vite, Python, Keras, Tensorflow
• Learnings: Backend API development with Flask, constraint-based algorithms (backtracking with forward checking), image preprocessing with OpenCV, integrating machine learning models into web applications, React development, setting up conda environments

Designed and implemented a heuristic algorithm to batch and consolidate laboratory sample racks, exporting to CSV file and reducing manual workload

• Tech Stack: C++, Visual Studio
• Learnings: Heuristic algorithm design, sample frequency analysis, Visual Studio development environment, problem-solving in real-world applications

Developed a full-stack web application to manage inventory and volunteer demographic data for the Village Food Hub, a nonprofit food pantry located in Andover, MA

• Tech Stack: React, Typescript, Tailwind, Next.js, Prisma, PostgreSQL, Vercel
• Learnings: Full-stack web development, database management with PostgreSQL and Prisma, React component design, API routing and CRUD operations with Next.js, version control with Git, UI/UX design using Tailwind CSS, pair programming and team collaboration

Built a binary classification model to predict whether an individual earns more than $50K/year using demographic and work-related features, as part of the Machine Learning Foundations portion of the Break Through Tech AI program @ MIT

• Tech Stack: Python, Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, Jupyter Notebook
• Learnings: Data preprocessing (handling missing values, one-hot encoding, winsorization), data exploration and visualization, training and evaluating tree-based models (decision trees, random forests, gradient boosting), feature and model selection, hyperparameter tuning with grid search, interpreting class imbalance and fairness across demographics

Built a responsive and stylized application allowing users to add, edit, view, and delete blog posts

• Tech Stack: EJS, CSS, Node.js, Express.js, PostgreSQL, Visual Studio Code
• Learnings: Responsive web design, CRUD operations, EJS templating, CSS styling for user interfaces, Node.js backend development, Express.js routing and middleware, PostgreSQL database management

• Programming Languages: C++, C, Python, HTML, CSS, JavaScript*
• AI Libraries & Frameworks: Scikit-learn, Pandas, NumPy, Matplotlib, Tensorflow*, Keras*
• Web Development Libraries and Frameworks: Tailwind CSS, EJS, React*, Node.js*, Next.js*, Express.js*, Flask*
• Databases: SQL*, PostgreSQL*, Prisma*
• Development Tools: Jupyter Notebooks
• Other: Git, GitHub, Linux

*still learning!

• Email: ellahou567@gmail.com
• Linkedin: www.linkedin.com/in/ellahou/