David Brown is a Postdoctoral Associate in Cornell’s Food Systems and Global Change group. He has an interdisciplinary background in Informatics, Geo-information Science and Production Ecology. His research focuses on developing and applying data science methods and tools to address challenges in agriculture and environmental systems.
Prior to his current position, David was a Postdoctoral Associate at Cornell’s School of Integrative Plant Sciences, where he developed data synthesis approaches for participatory on-farm crop trials and natural language processing workflows to extract and integrate crop trait information from scientific literature.
Earlier in his career, he worked at Bioversity International as a Research Fellow, GIS Specialist, and Information Technology Specialist. His work there ranged from spatial data analysis and machine learning–based data synthesis for crop variety evaluation to the development of scientific software and data platforms supporting agricultural research and decision-making.
He is particularly interested in innovative data synthesis approaches that integrate multimodal datasets to support location- and context-specific decision-making in agricultural production systems.
In collaboration with a multidisciplinary group of scientists, David is currently working on the development of MERLIN, a modeling software for assessing the environmental and socioeconomic impacts of livestock interventions, funded by the Gates Foundation.
Selected Journal Publications
Brown D, de Sousa K, van Etten J (2023) ag5Tools: An R package for downloading and extracting agrometeorological data from the AgERA5 database. SoftwareX 21:101267.
Brown D, de Bruin S, de Sousa K, Aguilar A, Barrios M, Gómez M, Hernandez JC, Chaves N, Madriz B, Machida L, Mejía P, Mercado L, Pavón M, Rosas JC, Steinke J, Suchini JG, Zelaya V, van Etten J (2022) Rank-based data synthesis of common bean on-farm trials across four Central American countries. Crop Science.
van Etten, J., Abidin, E., Arnaud, D., Brown, E., Carey, E., Laporte, M.-L., López-Noriega, I., Madriz, B., Manners, R., Ortiz-Crespo, B., Quirós, C., de Sousa, K, Teeken, B., Tufan, H.A., Ulzen, J., & Valle-Soto, J. (2020). The tricot citizen science approach applied to on-farm variety evaluation: methodological progress and perspectives. Lima, Peru: CGIAR Research Program on Roots, Tubers and Bananas (RTB). RTB Working Paper. No. 2021-2
Brown D, Van den Bergh I, de Bruin S, Machida L, van Etten J (2020) Data synthesis for crop variety evaluation. A review. Agronomy for Sustainable Development 40 (4):25.
Ocimati W, Bouwmeester H, Groot JCJ, Tittonell P, Brown D, Blomme G (2019) The risk posed by Xanthomonas wilt disease of banana: Mapping of disease hotspots, fronts and vulnerable landscapes. PLOS ONE 14 (4):e0213691
Calberto, G., Blake, D., Staver, C., Carvajal, M. and Brown, D. (2018). The frequency and effects of weather events on banana productivity - results of a global survey. Acta Hortic. 1196, 179-186.
Van den Bergh, I., Ramirez, J., Staver, C., Turner, D.W., Jarvis, A. and Brown, D. (2012). Climate change in the subtropics: The impacts of projected averages and variability on banana productivity. Acta Hortic. 928, 89-99.
