AI and Food Insecurity Case Competition
The Center for AI in Business at Smith, in collaboration with the NourishNet NSF Convergence Accelerator and Artificial Intelligence Institute of Maryland, is launching the first university-wide AI case competition for undergraduate and master‘s students at the University of Maryland College Park.
The broad goal of this challenge is to understand how AI can help alleviate food insecurity within communities. Food insecurity is the focus of Governor Moore’s recent efforts on the ENOUGH Act and related Neighborhood Impact Grant to alleviate food insecurity. The theme also aligns well with UMD’s First Year Book – Poverty by America.
This video briefly introduces the case competition.
Videos describing each case can be found below.
This competition is open to ALL undergraduate and master‘s students at the University of Maryland.
Why participate in the competition? Here are five reasons:
- There will be prize money for the winning teams!
- Capital Area Food Bank is interested in hiring students as interns and has indicated that they are open to continuing these projects over the summer by hiring some interns from participating teams as well.
- We will circulate the best solutions in each case to several industry advisory board members, increasing the chances of students securing summer internships.
- All students who participate and submit entries will receive a certificate of completion.
- Participating in the “AI for Food Insecurity” challenge can be a useful component of your resume to signal your ability to work with teams, think outside the box on pressing issues facing society, and willingness to take on new challenges.
We are delighted that one of the largest food banks in the area, Capital Area Food Bank, has signed on as the main sponsor of the tasks in the challenge, providing questions, data and support.
Detailed descriptions of cases 1, 2 and 3 will be posted by March 7.
Case Descriptions
Case 1
Food insecurity is a complex issue. There are many who need help, but do not seek it. There are those who need food but do not know where to go for it. This case asks teams to design or develop an AI-based solution that can help those who need food understand where to go to get it.
Jason Ding
Webpage: https://jason-ding.com/
LinkedIn: http
Email: ding@umd.edu
Andy Li
LinkedIn: https://www.linkedin.com/in/
Email: andyli@umd.edu
Zoom info sessions: Wed Mar 12 1-2pm (Masters); Wed Mar 12 2-3pm (undergrads)
Case 2
Capital Area Food Bank has many partners such as grocery stores or farmers who provide food (vegetables, meat, etc.) that can be distributed to food pantries. Many of these partners (grocery stores, farmers, etc) have questions that need to be answered (i.e. “Where can we deliver food, what types of food are needed” etc). Currently, the organization opens “customer service tickets” to answer these questions, and this is a time- and person-intensive process. Can AI help in improving the efficiency of this process?
Hanwen Shi
Webpage: https://www.rhsmith.
LinkedIn: https://www.
Email : hwshi@umd.edu
Zoom Info Session
Undergraduate: Wednesday, March 12 from 7 to 8 p.m.
Graduate: Saturday, March 15 from 7 to 8 p.m.
Case 3
Capital Area Food Bank spends a large amount of time developing grant proposals, reports, presentations, blog posts, and social media content regarding the work they do. Can generative AI help do this more easily, better, faster?
Brandon Colelough
Webpage: https://brandoncolelough.com/
LinkedIn: https://www.linkedin.com/in/brandon-colelough/
Email: brandcol@umd.edu
Zoom Info Session
Undergraduate: Friday, March 14 from 2 to 3 p.m.
Specialty Master's: Friday, March 14 form 3 to 4 p.m.
Timeline
April 15, 2025: Teams submit their solutions.
April 24, 2024: Teams selected for the finals present their solutions to judges between 5 to 9 p.m. and winners are announced.