Over the summer, I worked on creating a website, allowing students to conveniently set up meetings to eat together. Moreover, this website also offers meeting times and locations itself via a machine learning algorithm. Matching uses common interests and common friends as parameters to try to find a suitable meeting for users. Additionally, all the users have the settings to adjust the algorithm as well, and they can rate the offered meetings to get better matches for the future. These features allow users to meet with other students they don't know about but who have similar interests, therefore creating new connections between people on campus.
To implement the website, I used the Python programming language, including the Flask framework for the backend server, Tensorflow and Numpy for the machine learning algorithm, SQLAlchemy and PostgreSQL for the database, Docker for deployment, and Tailwind CSS, with HTML, JavaScript, and CSS for the frontend design. Overall, it is a good tool for students to use to enhance communication with their peers on campus.