Interests: Farm data management | Farmer-centric on-farm experimentation | Precision agriculture

Dr. Louis Longchamps is an Assistant Professor of Digital Agronomy in the School of Integrative Plant Science, Soil and Crop Sciences Section at Cornell University. His research involves developing precision agriculture techniques, such as soil and crop sensing, to improve input use efficiency in field crops. He is also actively engaged in On-Farm Experimentation (OFE), where he collaborates with farmers to integrate digital tools that enhance decision-making for profitability and environmental sustainability.

Before joining Cornell, Louis worked with Agriculture and Agri-Food Canada, focusing on optimizing nitrogen management using remote sensing and variable-rate nitrogen application. He co-led a Living Laboratory initiative aimed at developing solutions with farmers to reduce agriculture's environmental impact on the St. Lawrence River ecosystem.

Louis earned his Ph.D. from Laval University, where his research focused on the spatial structure of weed populations in corn fields and the potential for site-specific weed management. He completed postdoctoral research in soil and crop sciences at Colorado State University.

His current work emphasizes co-creating solutions with farmers, focusing on digital agriculture to improve data management and on-farm decision-making.

Interests: Agronomic software development | Biophysical & Environmental data integration | On-farm experimentation improvement

Phillip Lanza is a doctoral student at Longchamps Digital Agronomy Lab (Farmers DataLab). His research focuses on developing software tools to enhance observational research in agronomic systems, mainly by integrating biophysical and environmental data to improve on-farm experimentation. Before pursuing his Ph.D., Phillip worked as a full-stack software engineer, founded several companies, co-founded a nonprofit, and spent some time working as a carpenter. 

He holds an MS in Precision Agriculture, a BS in Horticulture, and a BS in Information Systems and Decision Sciences, all from Louisiana State University. 

Outside of his academic work, Phillip enjoys reading, photography, cooking, spending time outdoors, and navigating the adventures of parenthood with his toddler.

Interests: Sustainable digital agriculture | Sensor technology integration | Interseeding and cover crop management

Alexander Yore is a graduate student in the Longchamps Digital Agronomy Lab (Farmers DataLab). With a background in electrical engineering from San Francisco State University, where he graduated Cum Laude, Alexander applies his technical expertise to solving agricultural challenges. His PhD research focuses on interseeding, the practice of planting cover crops between rows of field crops to improve soil health, nitrogen levels, and reduce weed growth.

Alexander, alongside master's student Siddhant Ahlawat, co-created the Crop Health Integrated Micro-Environment Sensor (CHIMES). This system combines three sensors to collect sunlight, soil moisture, temperature, and conductivity data. CHIMES allows for high-throughput data collection with a single push of a button, streamlining the process for researchers and farmers. By providing real-time insights, CHIMES helps inform decisions on weed control and cover crop management, supporting more sustainable farming practices.

Interests: farmer knowledge | on-farm experimentation | rural sociology

Katie Rohrbaugh is a graduate student in the Longchamps Digital Agronomy Lab (Farmers DataLab), working toward an MS/PhD in Soil and Crop Sciences research. Her Master's research aims to better understand how farmers in New York State experiment to develop sustainable farming techniques through on-farm experimentation.

Before joining Farmers DataLab, Katie studied History and Environmental Studies at Princeton University, where she researched the development of environmental and agricultural knowledge throughout the British Empire from the 19th to 21st century. She leverages her interdisciplinary background to develop methodologies that democratize research and accelerate sustainable agricultural development by collaborating with farmers and prioritizing their knowledge and expertise.

Turning Data into Decisions for a More Sustainable Agriculture

Abdelkrim Lachgar is a research engineer and data scientist with a passion for applying advanced analytics to real-world agricultural challenges. Holding a Ph.D. in environmental modeling and an engineering background, he combines deep technical expertise with a systems-thinking approach. His work focuses on integrating machine learning, geospatial analysis, and remote sensing to support more precise, adaptive, and sustainable farming practices.

At Cornell University, Dr. Lachgar contributes to interdisciplinary research that empowers farmer-led experimentation and data-driven decision-making. He is particularly interested in how digital tools and spatial models can uncover hidden patterns in crop performance, optimize input use, and drive innovation at the field scale. With a strong foundation in both research and application, Abdelkrim serves as a vital bridge between agronomic science, computational tools, and on-the-ground practice.