Rising Stars

Before Montreal became a global AI hot spot, the Faculty has been contributing to the field through the Centre for Intelligent Machines (CIM), and researchers like Professor Warren Gross and Arash Ardakani are carrying on this leading-edge work.

The fact that industry giants such as Google, Facebook and Microsoft all call Montreal home for their Artificial Intelligence research may be surprising to some, but it is nothing new to the many researchers at McGill’s Centre for Intelligent Machines (CIM), who have been contributing to the field for decades. Founded in 1985, CIM is an inter-departmental, inter-faculty research group that facilitates and promotes research on intelligent systems. In the thirty years since the centre launched, Montreal has seen a boom in AI-related investment and interest.

Among the many members and associates of CIM is Professor Warren Gross, Chair of the Department of Electrical and Computer Engineering and a Louis C. Ho Faculty Scholar. Professor Gross is openly excited by the emerging possibilities of this activity.“There is a lot of industry here now, which makes an ecosystem of people,” he explains. “We are not just doing this research to write papers. We are training students who will be absorbed into the local economy. There isn’t a brain drain happening, and that’s why it’s important to do AI research here at McGill.”

A McGill Success Story

One researcher working in this area is Arash Ardakani (PhDEng ’20), a McGill Engineering Doctoral Awards’ (MEDA) recipient in the Electrical and Computer Engineering Department. Originally from Iran, he came to Canada on the advice of a friend who told him it was “the best country in the world.” Ardakani summarizes his decision succinctly: “McGill is one of the best universities in the world, so as soon as I got the offer I accepted it.”

Now working under the direction of Professor Gross, Ardakani’s research is in Deep Neural Networks in AI, and has resulted in the publication of his first paper only one year after his arrival. The paper since became one of the year’s most downloaded papers in the field of Very-Large-Scale Integration (VLSI). What is even more remarkable is that Ardakani had no knowledge of the domain before his arrival. “I told Professor Gross I wanted to experience something new and he told me about the project,” Ardakani said. “I couldn’t have done it without Professor Gross.”

Ardakani also appreciates the role philanthropy has played in his achievements. “When you have a scholarship, you don’t have any other concern,” he said. “You can focus on your research.”

Research that Matters

One application for their work is improving the speed and reducing the power consumption of portable devices, such as iPhones. “We are trying to make it a bit faster, more accurate, more secure, and less energy consuming,” Ardakani says. The results of this work “are being implemented on real applications, real devices,” he beams.

A challenge that underscores Ardakani and Gross’ work with deep neural networks is dealing with the computational burden of AI to make it work in a more energy-efficient manner. There are two reasons for the need for this improvement, Gross says. The first is to help with the battery life of devices and objects. The other is to cut the energy use of the massive data centers that process AI-based functions. Boosting data center efficiency will have a huge environmental impact according to Professor Gross.

Ardakani echoes this sentiment, saying their work could have a “huge impact on society.” And he is quite specific about the society he wants to impact the most: “I want to stay here and help Canada because it is beautiful and good. And Montreal, in terms of AI, is the best. Every big company is opening their office here, and it shows that Montreal’s star is rising.”

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