Darlyn Gomez, Nuria Siddiqa, Yangmei Lu, Mekhribon Yusufbekova

"The current state of BMCC’s on-campus job search is unorganized, inefficient, and outdated -- job postings can be found on on various flyers, sites, and docs instead of a single place. Students are unaware of the opportunities the school offers, forcing many to seek employment outside, which usually will not be related to the students’ major."

Moise Smedly, Oswaldo De Los Santos, Alyssa Vigueras, & Jannatul Naima

An AI-assisted student dashboard complete with a campus map to help students find their classes and push for more social good by promoting clubs, student engagement, leadership, opportunity and awareness.

Daniel Furmanov, Bar Yaakov, Erick Torres (& Kevin Lu)

Our project is AI advisor, this project aims allow students to enter their CunyID to receive personalized advisement which can be either a plan for next semester that will than be sent to a real advisor for approval or provide compatible service programs the student can be referred to. Our technology can help by saving the time of not only the student but the advisor as well allowing for them to tackle difficult tasks. Our solution is to make education more accessible by allowing students to get advised for simple tasks at home and save time for all involved. The future direction of this project would be to integrate directly with Degreeworks allowing sharing a similar database as well as a method to easily upload pdf of active programs happening at BMCC allowing the AI to refer students to them accurately.

Riley Drcelik, Alan Reyes, Oussama Ait Daoud, Karyn Huston

Our project aims to improve the front entrance ID scanners of BMCC to verify identification. Currently, for members of the BMCC community to scan in, you either use your phone or physical id. Physical ID is wasteful, and while in theory using your phone is good we found that many students struggle when trying to get in. The software is buggy and isn't future-proof. There are also security issues in how you can simply give your phone to someone else to sneak people in. With face recognition, we avoid that problem and it's much faster than having to try your phone ID multiple times. Going forward, we'd like to fully integrate our system with the turnstyles themselves and run it on the BMCC servers, expanding the project schoolwide and possibly CUNY-wide.