AgTech II: ScanSpectrum - Spectroscopy Made Portable, Affordable, and Adaptable Read more about AgTech II: ScanSpectrum - Spectroscopy Made Portable, Affordable, and Adaptable This presentation gives an overview on the use of ScanSpectrum to improve accuracy and data collection in spectroscopy.
AgTech I: Crop Mapping and Mobile Data Collection Read more about AgTech I: Crop Mapping and Mobile Data Collection This presentation gives an overview on the application of AI to mapping of cropland presence.
Mateusz Urbańczyk Keywords global health food security data analysis AI AI Application Read more about Mateusz Urbańczyk Mateusz Urbańczyk is a Software Architect at Quantitative Engineering Design (QED.ai), a mission-driven company working in global health and food security. He specializes in complex systems and end-to-end data processing pipelines for geospatial and medical data with over 7 years of experience. He finished his M.S. in Computer Science at the University of Wroclaw, with additional research studies at EPFL. Mateusz speaks Polish, English, Spanish and French. He has published research in pure mathematics, and has traveled for work across four continents.
Training on Data Analysis and AI Application for ANR Projects in Cambodia: Estimating Crop Yields Gaps in Rice SDP Project Areas Read more about Training on Data Analysis and AI Application for ANR Projects in Cambodia: Estimating Crop Yields Gaps in Rice SDP Project Areas During the lockdowns and movement restrictions due to the COVID-19 pandemic, Cambodia: Climate Resilient Rice Commercialization Sector Development Program (Rice SDP) explored ways to remotely monitor project implementation with the support of the Global Agriculture and Food Security Program (GAFSP) funding.