Priscilla Adong

Priscilla Adong brings expertise in machine learning, environmental research and remote sensing to the ARC Hub for ICT. She is currently pursuing a PhD at University College Dublin (UCD), where her research focuses on applying machine learning and remote sensing techniques to improve air quality monitoring. Her work explores approaches including transfer learning and explainable AI to develop robust and scalable models for environmental applications.

As part of her doctoral research, Priscilla presented her work on explainable AI-driven domain adaptation for improving the cross-domain transferability of satellite-based PM2.5 estimation models at the 2026 IEEE International Geoscience and Remote Sensing Symposium (IGARSS) in Washington, DC.

Prior to her PhD, Priscilla worked with AirQo at Makerere University in Kampala, Uganda, most recently as a Research Associate Fellow. During her time there, she led machine learning-based calibration of low-cost air quality sensors across multiple African cities and contributed to research investigating the transferability of machine learning calibration models for PM2.5 sensors across Kampala, Nairobi, Antananarivo and Addis Ababa.

Priscilla is also an alumna of the International Visitors Leadership Program (IVLP), a U.S. Department of State initiative through which she represented Uganda alongside STEM leaders from 40 countries. In recognition of her academic achievements, she also received a Student Achievement Award from UCD's College of Science.