github

ABOUT
ME

MY NAME IS MICHAEL LEUNG. I am an incoming senior majoring in Computer Science at the University at Buffalo with hands-on experience in full-stack development and applied AI. I am currently interning at AI Republic, where I built data analytics and context systems for database-driven LLM applications. I am also developing Strangers, a full-stack social connection web application used to connect students through
shared meals. Driven by curiosity and a love for problem-solving, I thrive on
tackling complex challenges in mathematics and software development.

TECHNICAL SKILLS:

  • Python
  • C, C#
  • Java
  • HTML & CSS
  • JavaScript
  • React
  • Linux
  • SQL
  • MongoDB

PROJECTS

Strangers

Developed Strangers, a full-stack social connection web application designed to help students build community by pairing peers for shared meals based on survey responses and personal preferences. The platform has received $5000 grant from Brandeis University to continue development. Collaborated with a 5-member agile team to plan, design, and test user flows, ensuring a seamless user experience while maintaining strict standards for data privacy. Implemented key features including secure user registration and login, customizable preference filtering, and reliable data storage using React.js, Express.js, and Firebase.

React.js, Express.js, Firebase

Py-Graspi

GraSPI is a research project led by Olga Wodo, a researcher in Informatics and high-performance computing for materials design and manufacturing. It’s a software tool that computes descriptors for segmented microstructures and organic solar cells, thereby enhancing machine learning applications in material science. Developed using Python, the software transitioned from C++/C, incorporating advanced graph-based libraries for optimal performance and compatibility. This project was executed using agile methodologies by a collaborative team of five, culminating in a second-place win at the University at Buffalo's 13th Bi-annual Computer Science and Engineering Demo Day. The innovative approach and teamwork demonstrated in GraSPI not only facilitated precise computational analysis but also showcased the potential to drive forward advancements in organic material research.

Python, C/C++

macy's Price Tracker

Enables users to scrape product data from macys.com and track price changes over time through line graphs. The system is built using Python with Flask for the backend API, React and JavaScript for a responsive and interactive frontend, and MongoDB for efficient storage and retrieval of user-specific product data. By utilizing this project, users can easily monitor price trends, allowing them to make informed purchasing decisions based on historical data. The combination of these tools ensures a fluid experience from data scraping to visualization of price fluctuations.

Python, Flask, JavaScript, React.JS, MongoDB

AlgoRhythm Learner

Collaborated in a team of four, utilizing agile methodologies, to develop a software application that visually teaches various data structures and algorithms. The application, hosted on an Apache server with a PHP backend, features a SQL and PHP based database called PHPMyAdmin for managing user information. We utilized React.js and JavaScript to deliver an interactive and dynamic user experience. Users can register and log into their accounts to save and keep track of their learning progress.

JavaScript, React.JS, PHP, SQL

Sudoku Solver

This project allows users to engage with various Sudoku puzzles, offering the ability to reset and quickly solve them using the backtracking algorithm. The system is built using Python with Flask for the backend API, and React and JavaScript for a responsive and interactive frontend. By leveraging this technology stack, users can enjoy a seamless and efficient puzzle-solving experience, making it easy to explore, reset, and solve Sudoku challenges.

Python, Flask, JavaScript, React.JS

Wordle Multiplayer

Collaborated in a team of four to develop software that transforms Wordle into a multiplayer experience. Each correct attempt at a 5-letter word is tallied towards your points over a set time. Points are updated on our leaderboard using WebSockets for a real-time experience against other players. This project was constructed using Python and Flask for the backend API, with HTML/CSS and JavaScript for a responsive and interactive frontend. We utilized Docker to containerize and deploy the web application and to run MongoDB in a separate container. This setup ensures consistent and streamlined deployment processes, enabling users to enjoy a dynamic multiplayer twist on the classic word game.

HTML/CSS, JavaScript, Python, Flask, MongoDB, Docker

CONTACT ME

My Information

micleung168@gmail.com

917-330-4833