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Food Information Networks

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This project is funded by the National Institute for Food and Agriculture and focuses on addressing food insecurity at both the information and physical access levels. Our team of designers, computer scientists, and social scientists from multiple institutions are engaging in a multiple phase project to thoroughly understand the barriers to access to healthy food, develop technological supports, and deploy and study our intervention in two cities – South Bend, Indiana, and Detroit, Michigan.

The project PIs are Ron Metoyer, Nitesh Chawla, Ann-Marie Conrado, and Danielle Wood of the University of Notre Dame, and Tawanna Dillahunt of the University of Michigan. Community partners include Beckie Lies (Purdue Extension), Gillian Shaw and Michelle Sawwan (enFocus), Sue Taylor (Beacon Community Impact), and Robin Vida (St. Joseph

Media

Publications

  • Szymanski, A., Jo, J., Sawwan, M., Eicher-Miller, H. A., Conrado, A.-M., Wood, D., Dillahunt, T. R., & Metoyer, R. A. (2026, April). Balancing goals, health, and cost: A food information system for managing complex choices and fostering sustained food agency. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (pp. 1–27). ACM.
  • Germino, J., Szymanski, A., Eicher-Miller, H. A., Metoyer, R., & Chawla, N. V. (2024). Corrigendum: A community focused approach toward making healthy and affordable daily diet recommendations. Frontiers in Big Data, 7, 1396638.
  • Szymanski, A., Wimer, B. L., Anuyah, O., Eicher-Miller, H. A., & Metoyer, R. A. (2024, May). Integrating expertise in LLMs: Crafting a customized nutrition assistant with refined template instructions. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (pp. 1–22). ACM.
  • Wimer, B. L., Szymanski, A., & Metoyer, R. A. (2024, May). Beyond static labels: Unpacking nutrition comprehension in the digital age. In Proceedings of the 2024 CHI Conference on Human Factors in Computing Systems (pp. 1–15). ACM.
  • Dillahunt, T. R., Sawwan, M., Wood, D., Wimer, B. L., Conrado, A.-M., Eicher-Miller, H., Gura, A. Z., & Metoyer, R. (2023, April). Understanding food planning strategies of food insecure populations: Implications for food-agentic technologies. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems (pp. 1–22). ACM.
  • Germino, J., Szymanski, A., Metoyer, R., & Chawla, N. V. (2023). A community focused approach towards making healthy and affordable daily diet recommendations. Frontiers in Big Data, 6, 1086212.
  • Marshall, J., Jimenez-Pazmino, P., Metoyer, R., & Chawla, N. V. (2022). A survey on healthy food decision influences through technological innovations. ACM Transactions on Computing for Healthcare (HEALTH), 3(2), 1–27.
  • Tian, Y., Zhang, C., Metoyer, R., & Chawla, N. V. (2021, October). Recipe representation learning with networks. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management (pp. 1824-1833).
  • Tian, Y., Zhang, C., Metoyer, R., & Chawla, N. V. (2022). Recipe recommendation with hierarchical graph attention network. Frontiers in big Data, 4, 778417.