Sanaa Hobeichi

Dr. Sanaa Hobeichi is a Senior Research Fellow at the University of New South Wales (UNSW Sydney), affiliated with the ARC Centre of Excellence for the 21st Century Weather. She serves as co-chair of the ACCESS-NRI Working Group on Machine Learning in Weather and Climate, driving national initiatives to integrate AI into Australia's weather and climate modeling infrastructure.

Her research program bridges Machine Learning, Climate Science, and Environmental Engineering to address critical challenges in climate downscaling and drought analysis. Key focus areas include developing high-resolution precipitation isotope models, hierarchical diffusion frameworks for climate downscaling, and machine learning systems for urban wind flow prediction. Her multidisciplinary expertise spans Applied Mathematics, Computer Science, and Climate Science, enabling innovative solutions for Australian-specific climate challenges like drought monitoring and energy demand forecasting.

Analysis of her recent publications reveals a dominant trend in applying cutting-edge machine learning techniques—including generative adversarial networks, diffusion models, and transformer architectures—to climate downscaling and drought modeling. Her work consistently targets Australian environmental systems, with strong emphasis on spatial statistics, temporal variability correction, and practical applications for weather prediction and water resource management.

As co-chair of the ACCESS-NRI Working Group, Dr. Hobeichi leads collaborative efforts to advance machine learning integration in national weather systems. Her work at the ARC Centre of Excellence fosters cross-disciplinary partnerships to enhance climate prediction capabilities, directly supporting Australia's resilience to extreme weather events through data-driven methodologies.