Sayma Shammi

Sayma Shammi is a Research Fellow at the University of Southern Queensland's School of Agriculture and Environmental Science. Her work focuses on integrating artificial intelligence and agricultural technology to enhance crop monitoring and climate resilience through innovative methods like UAV-based imaging and infrared thermography.

• BSc, North South University
• MSc, North South University
• PhD, Murdoch University

Her research interests include artificial intelligence, machine learning, computer vision, and image processing in agriculture. She applies these technologies to early frost detection, water stress monitoring, and plant stress analysis using machine learning algorithms and remote sensing techniques.

Recent publications highlight trends in precision agriculture, leveraging UAVs, multispectral imaging, and thermal data for crop health analysis. These works emphasize predictive modeling, climate adaptation, and data-driven farming solutions.

• ACS 1962 Medal (2023-2024) for outstanding doctoral research in Information Technology and Computer Science
• Vice-Chancellor's Gold Medal from North South University for academic excellence

She has nine years of tertiary teaching experience, currently instructing AGR3105 Smart Data Farming, and collaborates with the Institute for Resilient Regions (IRR) at USQ to advance digital agriculture through technological innovation.