Abstract: Big data has become a ubiquitous watchword of biomedical innovation advocating the deployment of advanced data-driven artificial intelligence techniques and systems thinking to revolutionise biomedical research and practice. AI-empowered Biomedicine Laboratory led by Dr Vafaee develops cutting-edge innovative machine-learning and network science methodologies to leverage large-scale molecular and clinical data to find hidden structures within them, account for complex interactions among the measurements, integrate heterogeneous data and make accurate predictions in different biomedical applications. In this talk, Fatemeh overviews the main themes in her research program from minimally-invasive biomarker discovery for personalised medicine and single-cell sequencing data analysis to computational drug repositioning and network pharmacology. Across all themes, Dr Vafaee’s research heavily relies on multidisciplinary expertise and cross-faculty collaborations to generate translatable outcomes impacting upon biomedicine of the future.
Bio: Dr Fatemeh Vafaee is the Deputy Director of the Data Science Centre at the University of New South Wales (UNSW Sydney) and leads the ‘Health Data Science’ priority area. She launched and leads Artificial Intelligence in Biomedicine Laboratory (VafaeeLab.com) at UNSW and is the founder of OmniOmics.ai proprietary limited company (OmniOmics.ai) with the mission to develop and deploy AI technologies to enhance disease diagnosis and accelerate drug development. Dr Vafaee received her PhD in Artificial Intelligence from the School of Computer Science at the University of Illinois at Chicago, USA (2011) followed by 2 multidisciplinary postdoctoral fellowships at the University of Toronto, Canada, and the University of Sydney, Australia (2012 – 2017) on computational biomedicine. Dr Vafaee has a strong track record of multidisciplinary research leadership and industrial engagement. Her research has attracted over $10.5M across >12 research and industry-based project grants and has been published in top-tier journals in the field.