Daniel
Jimenez Rodas
Agronomy
Agriculture
Research for Development
Research Data Mining
Big Data
Machine Learning
Artificial intelligence
Data analysis
Climate Change
Biography
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).
Projects
Digitization of small-scale agriculture
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
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
Aquileo Gonzalez de León
Ricardo Alexander Peña Venegas
Oscar Estrada Vargas
agronomy statistics digital agriculture
