September 23 to 25, 2022
AI for Good is a 48-hour hackathon bringing together UNF student teams, and partners JEA, FIS, and Microsoft to build solutions that drive social and environmental benefits.
The hackathon was organized using Devpost. Follow the below Devpost link to view winners, judging criteria, rules, and schedule.
Over the course of a weekend, UNF students collaborated to work on unique problems impacting the environment. Students were provided with the tools, support, and data needed so that they can write the code to right the world.
Participating students received mentorship from FIS, Microsoft, JEA, and UNF experts. Participants were expected to use their skills in the problem domain, programming, data mining, machine learning, statistical analysis, and visualization techniques to solve the problem. Hackathon participants were expected to form a team with a maximum of three to work on the hackathon problems and datasets.
David Berglund, Global Head of AI at FIS, recorded and produced a video highlighting the hackathon event. LinkedIn post containing the video can be accessed at LinkedIn Post
JEA provided two problem areas and relevant datasets for student teams to work during the hackathon.
Predict solar farm power generation given historical data.
Optimize a vehicle routing problem given starting location, ending location, and a number of maintenance stops that must be made.
FIS was the lead organizer for the hackathon event handling logistics, food, and prizes.
Microsoft provided access to Azure services and in-house support to use Azure technologies to solve the hackathon problems. Microsoft covered costs for prizes.
Friday, September 23
Saturday, September 24
Full day of coding and hacking remainder of the day and through the night
Sunday, September 25
Predicting Future Solar Power Output from NOAA Weather Data
by Jeremy Cantor, Aidan Doruska, and Jack Swingle
Solar prediction: Predict solar farm production from weather
by Marion Forrest, Troy Kidd, and Jason Swinehart
PF: Your optimal pathfinder
by Michael Kimollo, Prajwol Lamichhane, and Kris Roker
Jeremy Cantor, Aidan Doruska, and Jack Swingle
Marion Forrest, Troy Kidd, and Jason Swinehart
Michael Kimollo, Prajwol Lamichhane, and Kris Roker
Hackathon Check-in
Vehicle Route Optimization Problem Description
Predicting Solar Power Generation Problem Description
Kickoff Event Audience
Hackathon Cruise Director Carole
Vehicle Solutions Team
MJR Team
Mentoring on Azure Technologies
Volunteers Hangout
Star Team
Mentoring on statistical Approaches
MelNazSharif Team
MelNazSharif Team Presentation
Hackathon Judges
Vehicle Solutions Team Presentation
Hackathon Judges
Adjective Animal Team Presentation
Sunflower Squad Team Presentation
Award Ceremony Group Picture
Ashish Talati
Microsoft
Steve Lindsey
Microsoft
David Berglund
FIS
Matt Berseth
NLP Logix
Timothy Hunt
JEA
Dr. Lakshmi Goel
UNF
Each participating team was evaluated on their model performance and presentation of the results. Winners of the hackathon was determined based on the below evaluation weightings and ratings.
Presentation (20%)
Model Performance (40%)
Solution Approach (40%)
5 = Excellent presentation on all counts
4 = Very good presentation with minor issues
3 = Pitch can be significantly improved but is satisfactory overall
2 = Pitch is incomplete and severely lacking
1 = Presenter fails to address the criteria
Gary Duma
FIS
Santosh Metla
FIS
Sheel Saket
FIS
Greg Happ
FIS
Greg Harvey
JEA
James Haley
JEA
Halley Den Nys
JEA
Steve Lindsey
Microsoft
Ashish Talati
Microsoft
Dr. Xudong Liu
UNF
Dr. Indika Kahanda
UNF
Dr. Michelle DeDeo
UNF
Dr. Richard Shang
UNF
Kayla Drake
Connor Geller
Ryan Dey
Brandon Dinh
Rachel Aguinaldo
Amna Mehmood
Matthias van Meurs
Carter Johnston
Logan Hacker
Marcus Tervine
George Shannon
Cameron Davis
Alexa Zervos
Amanda Cross