Hi, I'm Luca Orofina, a Computer Science student at Queens College with experience
in developing applications using Python, JavaScript, and SQL.
Currently I am working on a Patient Service Web App using a MERN tech stack for a small private clinic.
My goal is to enter the tech industry as as a fullstack developer.
I would like to gain knowledge and experience in software engineering and
web app development.
Currently I am working at a restaurant while studying at CUNY Queens College.
In February, I began a Fullstack Software Development program at CUNY Queensboroough
Community College where industry experts teach us how to use popular development tools and
technologies, while getting hands-on experience by creating projects while collaborating on
a large group project.
I am trying to gain experience by freelancing on the side, developing applications for small businesses.
I also dabble in RaspberryPI and Arduino, I would love to get more into robotics in the future, there is something about seeing your software turn into something physical that inspires me.
My group and I worked on a project for our Software Engineering class (CS 370) we used a machine learning algorithm known as Random Forest to determine the quality of a wine based on its attributes. We used a large dataset to "teach" the algorithm what qualities made wine good, and which made it bad quality.
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My dark mode Chrome extension toggles a webpage's background by injecting CSS through a button click, with JavaScript, HTML, and CSS files kept separate.
Note: It must be update to Manifest V3 to be available in the chrome store.
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QCC Software Engineering Micro-Credential Career Track in Web Development Repository with a full-stack web application in collaboration with other members.
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This Web game project is the classic 'Brick Breaker' Game made with vanilla JavaScript. It uses simple physics logic to create movement and reactions, while also keeping track of the score and lives. Primarily I used the canvas element to render moving images, key controls and collision detection.
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