NEWLY HIRED STATS PROF BRINGS EXPERTISE IN BIG DATA AND MACHINE LEARNING

His recently published paper in Nature maps the genetic basis of human brain structure and function using data from over 500,000 participants of the UK Biobank consortium.

Elliott, along with researchers at the University of Oxford department of Statistics and the Wellcome Centre for Integrative Neuroimaging reported results on 148 associations between genetic variations and 3,144 different brain structure and function phenotypes derived from magnetic resonance imaging. They also reported on the heritability of these phenotypes, and compared the genetic pattern of this heritability with that of brain related traits and neuropathologies such as schizophrenia.

The results comprise the largest broad analysis of genetics in the brain, and will serve as a guide for new hypothesis about brain development, neurodegenerative disease and neuropathology. 

Elliott points out that it is only recently that computers have been able to handle computational burdens of this magnitude. “All of these new results in machine learning began to happen when academics started to use machine learning with bigger datasets and faster hardware,” he says.

In terms of consumer services, Elliott says that machine learning already has a massive impact on our daily lives. He cites an array of consumer services powered by machine learning such as Alexa, Siri, computer translation, personalized medicine, and self-driving cars.

Elliott is impressed that Canada has taken a leading role in the development of machine learning and he’s delighted by the opportunities that it will bring to his students.  “I've been so impressed by the caliber and drive of SFU students. The world is theirs,” he says.