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, while pursuing his Ph.D. in Internet of Things (IoT) at the African Centre of Excellence in IoT, University of Rwanda.

His research is fundamentally driven by the critical need for up-to-date and reliable crop production statistics across Sub-Saharan African (SSA) countries. Mr. António has observed that while machine learning (ML) and Earth Observation (EO) are effective for crop monitoring, their application is often hindered by the scarcity of in-situ data required for developing reliable models and producing timely agricultural information. His work therefore focuses on advancing ML and EO satellite imagery approaches to achieve accurate crop type classification and yield estimation within SSA smallholder farming systems.

To address these challenges, Mr. António is developing a physics-informed GeoAI-based framework at the Xylem Lab designed to significantly improve crop yield estimation by integrating the WOFOST crop model with Ensemble Kalman Filter-based leaf area index assimilation and a machine learning model. His doctoral research is supervised by professors from Carnegie Mellon University (CMU) Africa, where he is an active member of the GEOLAB research group, further strengthening his contributions to precision agriculture and geospatial AI.