Sanaa Hobeichi is a Senior Research Associate at the Climate Change Research Centre and the ARC Centre of Excellence for the weather of the 21st Century. She is interested in applying machine learning (ML) to advance climate and weather research. Her research focuses on using ML in climate downscaling and improving the prediction of weather and climate extremes.
Sanaa is the co-chair of the Machine Learning for Climate and Weather Community...view more
Sanaa Hobeichi is a Senior Research Associate at the Climate Change Research Centre and the ARC Centre of Excellence for the weather of the 21st Century. She is interested in applying machine learning (ML) to advance climate and weather research. Her research focuses on using ML in climate downscaling and improving the prediction of weather and climate extremes.
Sanaa is the co-chair of the Machine Learning for Climate and Weather Community Working Group at the ACCESS-NRI.
Sanaa has a background in Climate Science, Environmental Science, Applied Mathematics, and Computer Science and she is a former International Baccalaureate teacher.
My Qualifications
PhD Climate Science | UNSW Sydney
MSc Environmental Sciences - Major Remote Sensing | Qatar University
BSc Applied Mathematics - Major Computer Science | Lebanese University
My Research Supervision
Areas of supervision
Machine learning applications for weather and climate
Currently supervising
Ananya Anand - Honours
Thesis: Developing a Machine Learning model to generate high-resolution land surface temperatures for a city vulnerable to lethal heatwaves
Supervisory Panel: Prof. Katrin Meissner, Dr. Sanaa Hobeichi, Dr. Marzie Naserikia, and A/Prof. Negin Nazarian,
Husnain Asif - PhD
Thesis: Advancing climate model downscaling for southeast Australia by integrating latent diffusion models with NARCliM 2.0 ensemble
Supervisory Panel: A/Prof. Sarah Kirkpatrick, Prof. John Taylor, Dr. Sanaa Hobeichi
Supervisory Panel: A/Prof. Sarah Perkins-Kirkpatrick, Prof. John Taylor, Dr. Sanaa Hobeichi
https://orcid.org/0000-0001-6825-3854