Data Science for Agriculture and the Environment

Data Science for Agriculture and the Environment

10 octobre 2022

@Institut Agro, Montpellier (Building 11, Room 101)

Join the #DigitAg scientific seminar « Data Science for Agriculture and the Environment », with researchers from CGIAR (Alliance of Biodiversity International & CIAT)

During the visit of the CGIAR /Alliance of Bioversity International & CIAT « Digital inclusion » research group, #DigitAg is organising a hybrid seminar that will showcase presentations from :

CGIAR (Alliance of Bioversity International & CIAT)

  • Dr Daniel Jiménez, Senior Scientist at CGIAR
  • Dr Jacob van Etten, Principal Scientist and Director of the Digital Inclusion research program at the Alliance of Bioversity International & CIAT
  • Dr Louis Reymondin, Scientist at the Alliance of Bioversity International & CIAT
  • Dr Elizabeth Arnaud, co-leader of the Digital Solutions Teams, in the Digital Inclusion Lever, of the Alliance of Bioversity & CIAT

#DigitAg : 4 PhD students specializing in data sciences and artificial intelligence 

  • Léa Courteille, Inrae
  • Yulin Zhang, Institut Agro
  • Felipe Vargas Rojas, Inrae
  • Juan Pablo Rojas-Bustos, Inrae

Please find the preliminar program below (you can also download it through this LINK)

Please note attendance through visioconference is only possible at this point. Register now through this form.

Data Science seminar program

Daniel Jiménez (PhD) is a senior scientist at CGIAR. He is agronomist by training and for more than a decade has been working on topics related to digital agriculture; ranging from site-specific agriculture, data-driven Agronomy, artificial intelligence, Big Data and digital extension to real-Time monitoring of food systems. His work has received recognition from the World Bank Group (2015) and the United Nations (2014 and 2017), 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 the International University of Applied Sciences of Western Switzerland (HEIG-VD), and was also a consultant for the French Agricultural Research Centre for International Development (CIRAD).

 Publication highlights:

A data-mining approach for developing site-specific fertilizer response functions across the wheat-growing environments in Ethiopia. Cambridge University Press · 15 mars 2022
Artificial intelligence, systemic risks, and sustainabilityArtificial intelligence, systemic risks, and sustainability. ELSEVIER · 17 sept. 2021
Pronosticos AClimateColombia: A system for the provision of information for climate risk reduction in Colombia. Computers and Electronics in Agriculture · 1 mai 2020


JVan Etten

Jacob van Etten is Principal Scientist and Director of the Digital Inclusion research program at the Alliance of Bioversity International and CIAT. In his work, Jacob brings together insights and methods from the social, environmental and plant sciences. His research focus is on new digital solutions for agricultural citizen science, emergency management and rural extension. He uses user-centric digital design approaches to ensure new solutions embody two-way information flows between farmers and other decision-makers. Before joining Bioversity in 2012, he worked for Food and Agriculture Organization of the United Nations (FAO) in Mali, the International Rice Research Institute (IRRI) in the Philippines, and IE University in Spain. He is a Dutch national.

 Publication highlights:

Van Etten, J., Beza, E., Calderer, L., Van Duijvendijk, K., Fadda, C., Fantahun, B., Kidane, Y.G., van de Gevel, J., Gupta, A., Mengistu, D.K. and Kiambi, D., 2016. First experiences with a novel farmer citizen science approach: crowdsourcing participatory variety selection through on-farm triadic comparisons of technologies (tricot). Experimental Agriculture, early online.
Manners, R., and van Etten, J. 2018. Are agricultural researchers working on the right crops to enable food and nutrition security under future climates?." Global Environmental Change 53, 182-194.



Louis Reymondin is an expert in developing solutions that harness the power of Machine Learning to make sense of Big Earth Data. His background is in machine learning, software development sand remote sensing. Louis’ research focuses on the development and implementation of large-scale monitoring systems for near real time human impact assessment combining multi sources remote sensing data from moderate to very high resolution (UAVs). He did his undergraduate in software development (expertise in Java, Python, C++) at University of Applied Sciences Western Switzerland and followed a PhD program in Geography at King’s College London. Louis’ PhD research focused on the development and implementation of Terra-i: an early warning system to monitor changes in habitat throughout the tropic. Louis has 15 years of experience with the Alliance of Bioversity International and CIAT and is now co-leading the Data Driven Sustainability research program.

 Publication highlights:
Louis Reymondin, Paula Paz-García, Jhon Jairo Tello, Alejandro Coca-Castro, Oscar Bautista, and Bernadette Menzinger, 2019, User manual Near-Real-Time Monitoring System for the Detection of Vegetation Loss in the Tropics

Elizabeth Arnaud

Elizabeth Arnaud is co-leader of the Digital Solutions Teams, in the Digital Inclusion Lever, of the Alliance Bioversity-CIAT. Elizabeth leads the CGIAR Ontologies in Agriculture Community of Practice (CoP), which is now contributing to the new ‘Digital Information and Transformation’ Initiative of ONECGIAR. She also leads the ontology and metadata workstream of the Periodic Table of Food Initiative (PTFI). The CoP develops or contributes to ontologies on plant phenotyping, agronomy, fisheries and aquaculture, and socio-economics.


Publications highlights :

Elizabeth Arnaud, Marie-Angelique Laporte, Soonho Kim, ..., Erick Antezana, Medha Devare, Brian King, 2020, The Ontologies Community of Practice: A CGIAR Initiative for Big Data in Agrifood Systems, Patterns


Date de création : 18 juillet 2023