Team: Underdogs 

"Freshman RoadMap" is a portal that contains all the different information needed for a freshman to succeed and have a good academic year. After accepting to join BMCC on the CUNY First website one might feel left on your own to figure out what are the next steps are. Plenty of questions without answers that me and my peers went through starting off. In the future by keeping the same structure it could be use on any college campuses and also use as a group discussion for freshman or all.

Team: CUNY Coin

We are proposing an app that generates a QR code for CUNY students to be able to recycle their finished beverage products (Coca-Cola, Pepsi, Sprite, etc) via on-campus recycling machines that can receive user input and transfer crypto-funds to the designated account. 

The designated account will be the students' CUNY ID number

A workable app and website was created with a QR code embedded that can effectively scan for students to input their current CUNY ID information. The app then stores the information and tracks the input. 

Track: AI

Team Pantry Pals tied for 1st place! This team focused on the problem of food insecurity at BMCC. Pantry Pals is a website designed for Panther Pantry - a BMCC organization that provides nutritionally balanced non-perishable and frozen food for students facing a food emergency.  Their website allows students to place pick-up orders at Panther Pantry.  Harnessing the power of ChatGPT 3.5 - this team was able to create an AI-generated list of food recommendations based on the students' dietary restrictions.

Track: AI

Team Ravenclaw tied for 1st place! Ravenclaw decided to focus on the issue of misinformation and disinformation at BMCC by creating an app called Pixel Guard. By analyzing metadata, pixel patterns, and other subtle cues, this app can flag content that may have been artificially generated or tampered with. In turn, users can verify the authenticity of any content, detect subtle alterations, and deep fake technology to protect themselves from misinformation and manipulation!

Track: Data Science

Team Code Runs took on the challenge of Environmental Sustainability. Their project focused on the creation of a predictive/soil analysis AI model that will serve as a tool to solve unsuitable crop selection. The model is trained on parameters such as soil fertility, suitability, soil nutrients, physical properties, and environmental factors. Using this data, the model can provide a cost & profit analysis to offer guidance for the entire cultivation process!

Track: AI Innovation

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.

Track: AI & Data Science

Predictive Insights: Use AI-driven models to analyze economic data and predict the minimum wage that would enable individuals to meet basic needs, such as housing, food, and healthcare.

Track: Open Source AI Innovation

•What do clubs do with leftover food after meetings?

•How can students access food resources to solve their food problems?

•Connect clubs’ leftover food with students.

• Clubs notify the platform about available food.

• Students receive information about available food.

• Incorporate more AI elements

Team: CUNY Companion

Track: AI Tech

We designed an app that integrates AI with a geolocating app and schedule for CUNY students, prioritizing Accessibility issues such as: walking, hearing, seeing, and even color blindness with the colors we used. We also added features for safety, addressinf gender equity, and food uncertainty with PantherPal.

Team: AccessAble

Track: AI Software

It's a website made to help college students study more effectively — especially those with dyslexia, autism, or other learning differences. 

Our goal is to make learning easier, more inclusive, and personalized for every student.

Team: Aurora Logic

The solution is to develop a predictive model that uses weather and unemployment data as factors to forecast shelter demand and enable proactive resource deployment.