Q1 Investment Program (WU + WR) Data Science AI WUR present at AAAI-23

AI conferences, in contrast with natural sciences ones, are very competitive venues. Its a great achievement that WUR was present this year at the 37th AAAI conference on Artificial Intelligence, held in Washington, DC, February 8-14. PhD students Ilias Tsoumas and Jingye Han presented recent WUR AI innovations! Both are supervised by Prof. Ioannis Athanasiadis.

PhD student Ilias Tsoumas presented his work in the main program, at the AI for Social Impact Track, on evaluating digital agriculture recommendations with causal inference. Ilias leveraged agricultural knowledge together with yield and environmental data, and developed a causal AI model of a farm system to identify the impact of sowing recommendations on yield. The paper is open access on arXiv.

Guest PhD student Jingye Han presented his paper in the workshop on “AI for Agriculture and Food Systems”, a prestigious event that aims to report on recent progress in AI can help transform agriculture by developing approaches that can uncover, model and predict complex relationships between environment, management, and genotypes.

Jingye presented DeepOryza, a knowledge-guided machine learning model for rice growth simulation that directly learns crop growth patterns from data! The paper is open access on OpenReview.