Jimenez Rodas

Agronomy Agriculture Research for Development Research Data Mining Big Data Machine Learning Artificial intelligence Data analysis Climate Change


Daniel Jiménez is a scientist at the Alliance of Bioversity International and CIAT and head of Agronomy at Universidad ICESI.  He is agronomist by training and has been a pioneer of using artificial intelligence techniques for agricultural research in developing countries. He leads the Data-Driven Agronomy Community of Practice of the CGIAR Platform for Big Data in Agriculture. His work has received recognition from the World Bank Group (2015) and the United Nations (2014 and 2017), he took the top prize at the Syngenta Crop Challenge in Analytics 2018 and the INFORMS 2020 Innovative Applications in Analytics Award competition. He holds a PhD in Agriculture science from Ghent University, he worked at Bioversity International and the University Of Applied Sciences Of Western Switzerland (HEIG-VD), and was also a consultant for the French Agricultural Research Centre for International Development (CIRAD).

Fellow researchers


Brian Bulla Caro

Electronics solar energy charging systems automation mechatronics pneumatics oleohydraulics mechanics soil sensors agroclimatic sensors mechanical design IOT telecommunications robotics

Oriana Michelle Gomez Muñoz

Wireless Sensor Networks IoT and Cloud Computing precision agriculture and smart tecnologies for environment System Engineering Programming languages (Java C ++) Databases (DB2 MySQL Oracle) Data Warehouse (DataStage) Operating Systems (AIX Linux Windows) Artificial Intelligence Software Engineering 3D animation (Blender) Graphic Design (Corel Draw PhotoShop)

Luis Armando Muñoz Borja

Knowledge Management Digital Agriculture Climate Change Plant breeding and plant propagation Agriculture Climate smart agriculture Family agriculture Gas emission Productive systems Rural Extension

Luis Sandoval

agricultural economics data science business analytics strategy food security food and agricultural policy

Hugo Andrés Dorado Betancourt

Statistics Machine Learnig Data Science Computational Optimization

Juan Camilo Rivera Palacio

Digital agriculture Machine learning Deep learning

Andrés Aguilar Ariza

agriculture remote sensing earth observation data machine learning

Daniela Salas Betancourt

Marketing and internacional business

Oscar Estrada Vargas

agronomy statistics digital agriculture
With the support of
Fondo Coreano de Alianza para el Conocimiento en Tecnología e Innovación (KPK)