I am a computer science student eager to learn from experienced mentors in the field of software engineering.
In my free time, I enjoy watching sports such as basketball and football, as well as listening to music!
Contributed to an open-source software used by the Bear Necessities Market food pantry to manage inventory, track anonymous visits, and generate usage reports for hundreds of students and community members.
Developed a microservice-based reporting system to separate reporting logic from core services, improving modularity and maintainability.
Integrated RabbitMQ to enable asynchronous, real-time data syncing across microservice databases for consistent visit and inventory tracking.
Implemented unit and integration tests using Mocha and Chai to ensure accurate, anonymized data reporting and reliable inter-service communication.
A Programming Languages Compiler Compiler that auto-generates code from a grammar file containing lexical, syntactic (BNF), and semantic rules, enabling users to build custom programming languages
Expanded the semantics section to allow for a new section that accepts user written Python code, generating corresponding code in both Python and Java
Implemented comprehensive bats tests for all 32 predefined languages, ensuring full test coverage and reliability
Deployed a Dockerized testing environment and integrated it with a GitHub Actions pipeline to streamline and optimize the testing process
A personal portfolio website that highlights projects, skills, and experiences, includes links to social media profiles, and offers a user-friendly inquiry form
Developed a modern and responsive portfolio website using HTML, CSS, and JavaScript, hosted on GitHub pages
Added a light/dark mode toggle that retains user preferences across page reloads and initializes based on the device's theme settings
Integrated a functional 'Contact Me' form that enables users to send messages directly through the website
A Flask website that enables users to discover trending new songs, view their Spotify account statistics, and generate personalized song recommendations to explore new sounds
Leveraged the Spotify API to deliver real-time account statistics to users
Automated the creation of a personalized Discover Weekly homepage for each visit, utilizing the most popular songs
Implemented features that display users' recent songs, top tracks, top artists, and recommended songs across various time frames, providing a comprehensive overview of their account