Rosita Shishegar

Dr Rosita Shishegar is a Lecturer in Artificial Intelligence and Digital Health in the School of Computing Technologies at RMIT University. She also holds appointments as an Adjunct Research Fellow in the Department of Electrical and Computer Systems Engineering at Monash University and an Honorary Scientist at Austin Health. Before joining RMIT, she was a Senior Research Scientist at CSIRO’s Australian e-Health Research Centre.

 

Her research brings together artificial intelligence, machine learning, biostatistics and neuroimaging to advance digital health and personalised medicine. She develops computational methods for analysing complex biological and clinical data, with a particular focus on understanding the onset and progression of neurodegenerative diseases, including Alzheimer’s disease, Huntington’s disease and Friedreich’s ataxia.

 

A central contribution of her work is the development of methods to harmonise cognitive assessments across international studies, enabling researchers to combine data collected using different testing protocols. Her current research also explores generative AI, synthetic biomedical data and digital twins to model individual disease trajectories and support more personalised approaches to prediction and monitoring.

 

Dr Shishegar completed her PhD in Electrical Engineering at the University of Melbourne, where she developed MRI analysis methods to investigate brain development.

 

Research and funding

 

Dr Shishegar is a Chief Investigator on projects funded through the Medical Research Future Fund’s Dementia, Ageing and Aged Care Mission and the NHMRC–AMED Dementia Collaborative Research scheme, serving as methodological lead for biostatistics and AI. These include the Cognition,  Optimised, Digitised, and Harmonised (C-ODH) platform for assessing and monitoring dementia and cognitive impairment, and research investigating biomarkers, therapeutic targets and modifiable risk factors for non-Alzheimer’s dementias.

 

She has developed research software platforms to support data harmonisation and disease prediction for clinicians and health researchers. Her work has also attracted competitive CSIRO support for industry-linked doctoral research, undergraduate research placements and data harmonisation tools.