With global food demand expected to rise by seventy percent by 2050, researchers across the world are searching for innovative ways to increase food production. For Phoenix ARCS Scholar  Xaimarie Hernandez Cruz, the answer lies in empowering small and novice farmers through better access to data-driven decision-making tools.

"My research is just one part of a broader initiative," Hernandez Cruz said. "The idea is that if we can empower small and novice farmers to enter the market and maintain themselves there, we’re one step closer to achieving that seventy percent increase in food production."

Hernandez Cruz, who recently earned her PhD in industrial engineering from Arizona State University, focused her doctoral work on helping small farmers plan more effectively. Her research centers on building machine learning–based market intelligence systems that anticipate disruptions in the agricultural market—events like food trends, scarcity issues, or outbreaks that can impact supply and demand.

"A lot of times, when we talk to these growers, what they ask is: what should I plant?" she explained. "We help answer that question—what to plant, how much to plant, and when to plant—so they can maximize yield and profitability."

While existing frameworks considered past market conditions, Hernandez Cruz recognized a critical gap: the need to predict future market conditions. Using tools like Google search trends, social media data, and import/export data, she developed systems capable of identifying market disruptions months in advance. For example, she pointed to a major celery shortage in 2019, where her system could have detected the coming spike in demand well before it affected prices.

"It’s beneficial for consumers—ensuring affordable, nutritious food—but it’s especially critical for small and novice farmers," she said. "It gives them a chance to enter the market at opportune times."

Another major component of her work was addressing the scarcity of public agricultural market data.

"There’s a lot of private repositories, but they’re either proprietary or very costly to access," Hernandez Cruz explained.

To bridge this gap, she developed AI models to forecast missing data, allowing her tools to be applied across all regions of the United States—not just a select few.

Hernandez Cruz’s passion for this work is rooted in her personal experience growing up in Puerto Rico.

"My community flooded on a yearly basis, so I became passionate about using data science for social good," she said.

After Hurricane Maria devastated Puerto Rico, she witnessed firsthand the dangers of disrupted food supply chains, fueling her desire to pursue agricultural research that could make a difference.

The ARCS Foundation played a pivotal role in supporting her journey.

"The ARCS Foundation’s funding was very important," Hernandez Cruz said. "It allowed me to focus more on my research, talk to more practitioners, attend conferences, and expand the scope of my work. Without it, many of those opportunities wouldn’t have been possible."

As she looks to the future, Hernandez Cruz hopes her work will continue to support small farmers, helping them thrive in an increasingly unpredictable world.

"By helping farmers make more data-driven decisions, we can take a big step toward a more resilient and equitable food system," she said.