Projects
Webscraper
I built a web scraper using Python and the Selenium module to automate the extraction of financial analysis data for publicly traded company stocks. By simulating browser actions, the scraper navigates through financial websites such as Yahoo Finance.
​The scraped data is stored in structured formats like CSV or JSON for further analysis. This tool demonstrates the integration of web automation with data collection for financial insights.


YouTube Content Analysis Pipeline (Natural Language Processing)
​Built a full-stack analysis pipeline for YouTube content using the YouTube Data API to collect video and comment metadata at scale. Applied BERTopic to extract key themes from transcripts and comments, and fine-tuned spaCy for custom NER to identify players, teams, and officials in basketball commentary. Integrated sentiment analysis to assess audience reception and developed interactive dashboards to visualize engagement patterns, content performance, and entity trends.
Emoji Smash
Utilizing socket.io for synchronous updates, I built a digital version of the classic, Smash a Mole arcade game. Emoji Smash is a browser-based game where users select an emoji and try to click it as it moves randomly within a grid. A custom mallet cursor follows the user's mouse and animates on click for a satisfying smash effect. The game uses Socket.IO to enable synchronized updates and real-time interaction across multiple users.
Link Aggregator Site
My first project involving multiple users and local databases, this site aggregator website includes user authentication to ensure secure access to personalized content. It uses the bcrypt.js library to salt and hash user passwords before storing them in a MongoDB collection, enhancing security by protecting against plaintext password leaks. The website allows users to register and log in, with the backend built using Node.js and Express. Upon registration, user credentials are hashed with a unique salt, and on login, the entered password is compared with the stored hash. MongoDB is used to manage user data and aggregated site content, offering a scalable and efficient solution for storing structured information.
