October 16th is World Food Day, a global campaign that celebrates the founding of the Food and Agriculture Organization 80 years ago and works towards a healthy, sustainable and food-secure future. More than 670 million people worldwide face hunger. Millions of other people face rising obesity rates and struggle to eat healthy foods to get proper nutrition.
World Food Day calls on governments around the world, as well as businesses, academia, the media and even young people, to take action to promote resilient food systems and fight hunger. This year, the Abdul Latif Jameel Institute for Water and Food Systems (J-WAFS) is spotlighting MIT researchers working toward this goal by studying food and water systems in the Global South.
J-WAFS Seed Grants fund early-stage research projects specific to previous research. The 11th round of seed grants in 2025 supported 10 MIT faculty to conduct cutting-edge water and food research. Dr. Ali Aouad ’17, assistant professor of operations management at the Massachusetts Institute of Technology Sloan School of Management, was one of these grant recipients. “Before I came to MIT, I was looking at what research centers and initiatives were available that were trying to integrate food systems research,” Aouad says. “So we were very excited about J-WAFS.”
Mr. Aouard gathered more information about J-WAFS during a new faculty orientation session in August 2024, where he spoke with J-WAFS staff and learned about the program’s funding opportunities for water and food research. Later that fall semester, he attended several J-WAFS seminars on agricultural economics and water resource management. It was then that Aouard realized that his project was perfectly aligned with J-WAFS’ mission to secure water and food for humanity.
Aouad’s Seed Project focuses on food subsidies. With a background in operations research and an interest in digital platforms, much of his work has focused on tailoring supply-side operations to the preferences of disparate customers. Past projects include projects on retail systems and matching systems. “We started thinking that this kind of demand-driven approach might also be very relevant to important social challenges, especially around food security,” Aouard says. Before earning his PhD at the Massachusetts Institute of Technology, Mr. Aouad worked on a project examining subsidies for smallholder farmers in low- and middle-income countries. “I think in the back of my mind I’ve always been fascinated by trying to solve these problems,” he said.
His seed grant project, Optimal Subsidy Design: Applications to Food Assistance Programs, aims to leverage data on the preferences and purchasing habits of local grocers in India to inform food aid policy and optimize subsidy design. Common data collection systems such as POS are not readily available in local grocery stores in India, making it difficult for low-income earners to obtain this type of data. “Independent stores are very important last-mile operators when it comes to nutrition,” he explains.
For this project, the research team provided local grocery stores with POS scanners to track purchasing habits. “We aim to develop algorithms that convert these transactions into a kind of ‘reveal’ of an individual’s underlying preferences,” says Aouad. “Food assistance programs can therefore be modeled and optimized taking into account expected demand uptake and how much variety and flexibility they provide.” He adds, “Of course, the ability to answer detailed design questions (across different products and prices) will depend on the quality of the inferences from the data. Therefore, more sophisticated and robust algorithms are needed in this area.”
Following data collection and model development, the ultimate goal of this research is to inform policy surrounding food assistance programs through an “optimization approach.” Aouad explains the complexities of using optimization to guide policy. “Policy is often informed by disciplinary expertise, legacy systems, or political deliberations. Many researchers are building rigorous evidence to inform food policy, but it’s fair to say that the kind of approach I’m proposing in this study is not one that is commonly used. I see an opportunity to bring new approaches and methodological traditions to problems that have been at the heart of policy for decades.”
Consumers’ overall health is the reason food assistance programs exist, but long-term nutritional impacts and changes in purchasing behavior are difficult to measure. Aouard has noted in previous research that the short-term effects of food aid interventions can be significant. However, these effects are often short-lived. “This is an interesting question, and I don’t think it can be addressed within the scope of the interventions we’re looking at. But we want to capture it in our research. It might generate hypotheses for future research about how we can change nutrition-related behaviors over time.”
His project is developing new methodologies for coordinating food assistance programs, but large-scale application is not promised. “A lot of the drivers of subsidy schemes and food assistance programs are also, frankly, how easy it is and how cost-effective it is to implement these policies in the first place,” Aouad commented. There are unavoidable cost and infrastructure barriers to sustaining this type of policy research and program. While Aouard’s work provides insights into customer preferences and subsidy optimization in a pilot setting, replicating this approach at real scale can be costly. Aouad wants to be able to collect proxy information from customers to feed into models and provide insights into more cost-effective ways to collect data for large-scale implementations.
There is still much work to do to ensure food security for all, including advances in agriculture, food assistance programs, and ways to increase adequate nutrition. As the 2026 seed grant deadline approaches, J-WAFS will continue its mission to support MIT faculty pursuing innovative projects that have a practical and real-world impact on water and food system challenges.
