What sparked your interest in robotics, and how did your journey lead you to this field?
I’m not actually a roboticist, which may seem unusual given that I study in a robotics lab. Our work extends far beyond building robots: We draw on software, biology, data science and outreach to solve agricultural challenges.
After earning a bachelor’s degree in communications and earth science in 2011, I worked in public relations producing multimedia content and managing websites. That experience led me into web development, software engineering and eventually web-based mapping tools. In 2015, I founded Orbitist LLC to focus on spatial software while continuing freelance work as a video producer for the Roger Tory Peterson Institute of Natural History.
A filming trip to Costa Rica had a lasting impact on me. While documenting wildlife in the rainforest, I became equally interested in the surrounding agricultural landscapes and the tradeoffs between conservation and farming. That curiosity led me to Cornell’s Lake Erie Research and Extension Laboratory, where I joined the Efficient Vineyard project in 2016.
What began as video production and website development evolved into helping build My Efficient Vineyard (myEV), an open mapping platform designed to make spatial data more accessible to growers and researchers. Over time, I became increasingly involved in precision agriculture, spatial data processing and agroecology. In 2022, my wife and I purchased land and started a small U-pick farm growing flowers and grapes.
In 2024, I began a NASA Acres-funded Ph.D. with Dr. Yu Jiang. Today, I am focused on advancing myEV, now rebranded as Every.Farm, into a scientific platform that supports remote sensing, AI and agricultural research.
What problems are you working to solve right now, and what approach or tools are you using?
I am interested in how emerging technologies can help create agricultural systems that are more profitable, environmentally beneficial and capable of producing nutritious food. My current focus is crop diversification.
Many agricultural regions have become highly specialized around a small number of crops. While those systems can be productive, they can also leave farmers vulnerable to changing markets, extreme weather and other risks. In western New York, for example, Concord grape growers have experienced declining returns for decades as demand has shifted and production has increased.
To address that challenge, our team is using AI to help build a comprehensive crop database: crops.every.farm. We are exploring how crop information can be combined with environmental, economic and farm-specific data to identify crops that may be well suited to particular locations.
When farmers consider introducing a new crop, they must weigh markets, soils, climate, infrastructure, labor and existing expertise. My research focuses on creating tools that help organize and analyze those variables so growers can make more informed decisions.
How do you hope your research will shape the future of robotics or the communities it serves?
My long-term goal is to better understand polycultures, or systems where multiple crops are grown together. Natural ecosystems such as forests provide an example of how diverse species interact in ways that create balance and resilience.
Modern agriculture often relies on monocultures, where a single crop dominates a landscape. While effective at producing yields, these systems can leave crops more vulnerable to pests, diseases and environmental stress.
Researchers have documented many benefits of crop diversity, but we still have much to learn about the mechanisms that drive those outcomes. My hope is that robotics, AI, remote sensing and automated data collection can help us better understand those processes and provide growers with practical tools for managing more resilient agricultural systems.
What do you wish more people in agriculture understood about the role robotics and AI could play in future food production?
Agriculture has a long history, and it is easy to assume that today’s production methods are inevitable because they have been so successful. But I believe it is important to step back and ask larger questions.
If we were designing agricultural systems from scratch using today’s technologies, what would farms look like? How would we organize crops, labor, logistics and infrastructure? Could farms generate ecological and cultural value alongside economic value?
For me, the most exciting aspect of AI and robotics is their ability to help answer those questions. The technology is not the goal. The goal is creating agricultural systems that better serve farmers, rural communities and ecosystems. AI and robotics may help overcome logistical, labor and management barriers that currently limit innovation and diversification.
At the same time, these tools carry risks. As researchers, we have a responsibility to identify potential harms and ensure these technologies are developed and deployed responsibly.
What’s one unexpected or little-known aspect of your research that might surprise people?
Many people are surprised when they see a robot operating in a real agricultural setting. But an even lesser-known fact is that every farm on Earth is regularly observed by satellites. Every few days, new imagery and environmental measurements are collected and made publicly available.
The amount of open agricultural data available today is remarkable, yet many growers and researchers still face challenges accessing and using it effectively. Part of what excites me about Every.Farm is the opportunity to make those datasets easier to explore and apply. The information already exists. The challenge is turning that data into useful knowledge and better decisions.
