15 citations · 42 across the 20 of their papers we have counts for
13 papers · 1 filter
Climate Variability Modulates the Impact of Price Spikes on Food Insecurity
Jordi Cerdà-Bautista, Vasileios Sitokonstantinou, Homer Durand +3
Climate variability influences whether a market disruption escalates into a food crisis, yet broad climate patterns like El Niño, tracked months before they alter hydro-climatic co…
Credit Access is Associated with Improved Food Security in the Horn of Africa
Jordi Cerdà-Bautista, Vasileios Sitokonstantinou, José Manuel Veiga López-Peña +3
The intensification of climate change poses a growing threat to food security, especially in vulnerable communities. This study employs an observational machine-learning framework…
Positive-Unlabeled Learning for Control Group Construction in Observational Causal Inference
Ilias Tsoumas, Dimitrios Bormpoudakis, Vasileios Sitokonstantinou +4
In causal inference, whether through randomized controlled trials or observational studies, access to both treated and control units is essential for estimating the effect of a tre…
Causal machine learning for sustainable agroecosystems
Vasileios Sitokonstantinou, Emiliano Díaz Salas Porras, Jordi Cerdà Bautista +8
In a changing climate, sustainable agriculture is essential for food security and environmental health. However, it is challenging to understand the complex interactions among its…
Causality and Explainability for Trustworthy Integrated Pest Management
Ilias Tsoumas, Vasileios Sitokonstantinou, Georgios Giannarakis +5
Pesticides serve as a common tool in agricultural pest control but significantly contribute to the climate crisis. To combat this, Integrated Pest Management (IPM) stands as a clim…
Assessing the Causal Impact of Humanitarian Aid on Food Security
Jordi Cerdà-Bautista, José María Tárraga, Vasileios Sitokonstantinou +1
In the face of climate change-induced droughts, vulnerable regions encounter severe threats to food security, demanding urgent humanitarian assistance. This paper introduces a caus…
Evaluating Digital Agriculture Recommendations with Causal Inference
Ilias Tsoumas, Georgios Giannarakis, Vasileios Sitokonstantinou +5
In contrast to the rapid digitalization of several industries, agriculture suffers from low adoption of smart farming tools. While AI-driven digital agriculture tools can offer hig…
Fuzzy clustering for the within-season estimation of cotton phenology
Vasileios Sitokonstantinou, Alkiviadis Koukos, Ilias Tsoumas +3
Crop phenology is crucial information for crop yield estimation and agricultural management. Traditionally, phenology has been observed from the ground; however Earth observation,…
Big Earth Data and Machine Learning for Sustainable and Resilient Agriculture
Vasileios Sitokonstantinou
Big streams of Earth images from satellites or other platforms (e.g., drones and mobile phones) are becoming increasingly available at low or no cost and with enhanced spatial and…
Evaluating Digital Tools for Sustainable Agriculture using Causal Inference
Ilias Tsoumas, Georgios Giannarakis, Vasileios Sitokonstantinou +5
In contrast to the rapid digitalization of several industries, agriculture suffers from low adoption of climate-smart farming tools. Even though AI-driven digital agriculture can o…
Personalizing Sustainable Agriculture with Causal Machine Learning
Georgios Giannarakis, Vasileios Sitokonstantinou, Roxanne Suzette Lorilla +1
To fight climate change and accommodate the increasing population, global crop production has to be strengthened. To achieve the "sustainable intensification" of agriculture, trans…
Pest presence prediction using interpretable machine learning
Ornela Nanushi, Vasileios Sitokonstantinou, Ilias Tsoumas +1
Helicoverpa Armigera, or cotton bollworm, is a serious insect pest of cotton crops that threatens the yield and the quality of lint. The timely knowledge of the presence of the ins…
Towards assessing agricultural land suitability with causal machine learning
Georgios Giannarakis, Vasileios Sitokonstantinou, Roxanne Suzette Lorilla +1
Understanding the suitability of agricultural land for applying specific management practices is of great importance for sustainable and resilient agriculture against climate chang…