Keiller Nogueira

Dr Keiller Nogueira is an academic staff member involved in teaching and research in machine learning and remote sensing. He coordinates the Applied Artificial Intelligence module (COMP534/COMP634) and has published extensively on data-centric ML for Earth observation, environmental monitoring, and public health applications.

• Module Co-ordinator for Applied Artificial Intelligence (2024-25)

Research Interests:
Dr Nogueira focuses on machine learning techniques for geospatial data, including imbalanced data handling, multi-task learning, and data-efficient approaches. His work spans land cover segmentation, urban health risk mapping, and environmental anomaly detection.

Publication Trends:
Recent articles highlight his integration of remote sensing with machine learning for precision agriculture, urban planning, and public health. Themes include contrastive learning, domain adaptation, and multi-sensor data fusion in environmental contexts.