Hi! I’m Erin Yoo.
I am a Software Developer, eager to leverage my full-stack development skills in real-world applications.
About Me
What I Do
I turn ideas into full-stack solutions with clean code and real-world impact
Frontend Development
Proficient in HTML, CSS, JavaScript, and React. I build responsive, accessible, and user-friendly interfaces with a focus on clean design and performance.
Backend Development
Experienced with Node.js, Express, and PostgreSQL. I develop scalable APIs, manage server-side logic, and design efficient database schemas.
Python Programming
Strong foundation in Python, with practical experience from academic and personal projects involving automation, data handling, and scripting.
Showcasing My Projects
Lace Up
Designed and built a full-stack e-commerce platform from scratch, featuring secure user authentication, dynamic product browsing, and detailed product pages. Leveraged React and Redux with RTK Query for optimized state management and 11 RESTful API endpoints, boosting data retrieval efficiency. Deployed on Netlify (frontend) and Render (backend), with email/password authentication to enhance security and user experience.
Fullstack
React
E-Commerce
Netflix Clone
Developed a detailed Netflix Clone web page utilizing HTML, CSS, JavaScript, and BootStrap, emphasizing a user interface that closely replicates the original Netflix layout with responsive design principles and provide a realistic browsing experience.
Web Development
BootStrap
Emotion Detection
Developed an emotion detection system to identify five distinct human emotions from video footage, leveraging OpenCV for facial recognition and image segmentation. Enhanced the model using Local Binary Patterns Histogram for texture analysis and contrast improvement, training it on a dataset of 250 images per emotion. Implemented real-time emotion recognition with confidence metrics, refining the system to stabilize unusually high confidence levels by 5% for improved accuracy.
OpenCV
Facial Recognition
App Design
Treasure Hunt
Built an interactive AI-driven game in Python where an AI agent competes against a human player to collect treasures on a 2D grid while avoiding traps. Implemented a Q-learning algorithm with an epsilon-greedy strategy, training the AI model over 10,000 iterations using reinforcement learning to optimize decision-making and reduce error rates. Designed a grid-based game landscape with treasures (‘T’), traps (‘X’), and vacancies (‘-’), enhancing gameplay through state-action rewards and refined AI decision processes.
Python
AI Learning
