Toronto’s Vector Institute announced today that it is adding 10 new faculty members, effectively doubling its size.
“Vector is a pillar of the Canadian AI ecosystem and I’m very excited that the team is expanding with highly sought-after talent, some of whom I’ve had the pleasure of working with,” said the Vector’s Chief Scientific Advisor Geoffrey Hinton. “Increasingly, the world’s most promising researchers in deep learning and other AI subfields are looking at Canada as a hub with many opportunities to collaborate, advance research and develop applications. This team will drive Vector’s excellence in research, education and industry collaboration.”
MIT postdoctoral researcher and Facebook PhD Fellowship recipient Jimmy Ba; 2017 AMIA Summit on Clinical Research Informatics (CRI) Best Student Paper nominee Marzyeh Ghassemi; and Professor Pascal Poulart of the David R. Cheriton School of Computer Science at the University of Waterloo are among those joining the Vector. The newcomers’ start dates range from autumn 2017 to August 2018.
The University of Toronto affiliated Vector Institute opened last spring with funding from the Canadian government’s CDN$125 million Pan-Canadian Al Strategy, the Ontario provincial government, and the private sector.
“Artificial Intelligence is an essential building block in today’s global economy – our government is ready to support Canada’s leadership role in this area,” said Canadian Minister of Innovation, Science and Economic Development Navdeep Bains. “The Vector Institute’s top-quality work is exactly what we need to continue growing Canada’s global reputation as a cutting-edge leader in AI research. Today’s announcement is no exception to the remarkable progress the Vector Institute continues to make.”
Over the last 20 years, Canada has contributed invaluable research achievements to the AI boom. Toronto and Montreal have played key roles in the rise of deep learning, and produced thousands of AI talents. The Vector Institute bridges academia, industry and institutions in the transformative fields of machine learning, deep learning and AI while providing researchers with opportunities to work with existing data sets to solve real-world challenges.
Journalist: Michael Sarazen