Associate Professor Fabio Ramos receives Sydney Research Accelerator (SOAR) Fellowship to continue ground-breaking work in intelligent machines.
Associate Professor Fabio Ramos' work in intelligent machines has been recognised with a Sydney Research Accelerator (SOAR) Fellowship. The real-world application of this research includes models to predict air pollution 24 hours in advance to data analytics for portable water production and asset management, and work applicable to mental health, mining and real estate.
“My research builds upon developments in mathematics, statistics and computer science to design algorithms that enable computers to understand data, make predictions about future outcomes based on historical data, and take intelligent decisions under uncertainty that maximise a given objective,” Associate Professor Ramos said.
“These methods and tools are known as machine learning.
“With the continuing development of data science, methods that can predict the outcome of events based on historical data are becoming increasingly powerful. However, it is unclear how to best utilise data science and probabilistic predictions to make informed decisions.
“My research aims to bridge the gap between predictions from big data to optimal decisions/actions.”
His work on air pollution forecasting aims to connect data science to statistical decision theory to answer key questions as to whether air pollution forecast models could be used to help define a policy and the benefits of investing in new monitoring stations. In healthcare, Associate Professor Ramos’ work aims to answer questions as to which treatments would lead to the best outcome given probabilistic predictive models of the patient’s recovery and whether we can provide theoretical guarantees for the optimality of these decisions.
“The SOAR fellowship will transform my profile by broadening the impact of the theoretical developments of my research to other fields, and to industry,” he says.
The research of Associate Professor Ramos has been pivotal towards the establishment of the Rio Tinto Centre for Mining Automation, which has attracted more than $35 million in research funding to the University and the Centre for Translational Data Science (CTDS), which aims to open unprecedented opportunities to apply the theoretical aspects of his research to fundamental problems in health, earth and biological sciences.
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