MIT EECS — Slaughter Undergraduate Research and Innovation Scholar
Generating MIT Course Recommendations Through A Latent Source Model for Collaborative Filtering
The goal of this project is to conduct research on collaborative filtering approaches and apply the knowledge to construct a class recommendation system for MIT undergraduate students. The vast number of courses offered by the Institute often beleaguers MIT students; they enter the university with general interests, but often do not know which classes provide the desired instruction. Each student’s trajectory of courses over the years can be represented as discrete time-series data, which can then be classified to formulate useful recommendations. This research project will conclude with an application in which students provide their interests and receive class recommendations based upon the trajectory of others students with similar backgrounds.
After taking 6.034 and 6.006, I developed a strong interest in data analysis and artificial intelligence. I also learned a wide variety of skills through internships at Ultimate Software and Celect but am now eager to learn more about collaborative filtering alongside Professor Shah. I am excited to construct an application that could be utilized by all MIT students to make the most of their educational opportunities.