Valinho António

Valinho António is a Visiting Scholar at the Xylem Lab in the Department of Geographical Sciences at the University of Maryland. Concurrently, he serves as a lecturer and researcher at Universidade Rovuma, Mozambique, and is pursuing his Ph.D. in Internet of Things (IoT) at the African Centre of Excellence in IoT, University of Rwanda.

Mr. António's research is driven by the critical need for up-to-date and reliable crop production statistics across Sub-Saharan Africa. While machine learning and Earth observation have proven effective for crop monitoring, their application is often hindered by the scarcity of in-situ data required to build reliable models and produce timely agricultural information. His work focuses on advancing ML and satellite imagery approaches to achieve accurate crop type classification and yield estimation within smallholder farming systems across the region.

To address these challenges, Mr. António is developing a physics-informed GeoAI-based framework at the Xylem Lab that integrates the WOFOST crop model with Ensemble Kalman Filter-based leaf area index assimilation and a machine learning to improve crop yield estimation. This work is carried out under the supervision of professors from Carnegie Mellon University Africa, where he is an active member of the GEOLAB research group, further strengthening his contributions to precision agriculture and geospatial AI.