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How the Rotman School’s data scientist in residence is making sense of big data

April 12, 2019

Photo of Brian KengProfessor Brian Keng is on a mission.

“When it comes to artificial intelligence, people like to think of it as a type of magic,” says Keng. “Usually, they imagine it as a mix of what they learned in statistics class blended with a bit of science fiction.”

Keng, who is an adjunct professor and data scientist in residence at the Rotman School, wants to clear up some of the mystery around big data and artificial intelligence (AI) — and he might be the best person for the job. As chief data scientist at Rubikloud Technologies and having earned a PhD in computer science from U of T, he can easily grasp the relevant points from the latest academic research and understand their potential significance in a business context.

He’s bringing perspective, knowledge and some much-needed clarity on the data revolution and AI by leading and coordinating a series of lectures, events and hands-on activities at the School.

Putting data into context

By now, the business case for data has been made. Most organizations recognize why data should be considered when making business decisions and are aware of its value in prediction.

The next challenge is understanding the actual capabilities and limitations of new, emergent AI-related techniques.

Early on, the Rotman School anticipated a potential knowledge gap within the industry and quickly got to work launching a new Master of Management Analytics (MMA) program and the TD Management Data and Analytics Lab. Still, the School knew that it needed someone who could connect how industry, research and learning all fit together when it comes to data. This is exactly why Keng came on board. His first order of business was reassuring working professionals.

“Organizations that know how to analyze and leverage data effectively are going to have a competitive advantage.”

—Brian Keng, Data Scientist in Residence

“A lot of attention has been paid to the underlying math and modeling, but I want people to have a conceptual view of how these tools can be applied, and how they might serve a purpose in their work,” he says. “In that sense, data really is just like any new technology.”

Still, make no mistake that having a handle on data will be vital, says Keng.

“Roles will change, and everyone will likely need some level of data fluency,” he says. “Organizations that know how to analyze and leverage data effectively are going to have a competitive advantage.”

Giving Rotman a competitive advantage

Since joining Rotman in 2018, Keng has been actively trying to give students, faculty and the wider Rotman community that competitive advantage.

Recently, in a lecture for MMA students, he broke down what neural networks are and how deep learning works — essentially, how certain combinations of simple mathematical operations can enable machines to identify patterns and predict outcomes from massive data sets. Throughout these sessions, students feel comfortable enough to bring up questions or to ask him to slow down when the material gets too technical.

“The best part of this role has been working with students and business professionals who genuinely want to learn,” says Keng. “Because of the collection of diverse interests and backgrounds we have here, I’m seeing the different angles from which people approach data. It’s making me really consider the full breadth of data’s potential.”

Brian Keng on "Putting AI to Work"

He’s also worked on a number of projects aimed at getting the wider community interested in data analytics. Keng helped design the challenge problem for the School’s 2018 Datathon event, where participants were tasked with identifying key strategies for improving safety in the city by deriving insights from real data sets. He also invited a few of his professional contacts to speak at the School’s cybersecurity event earlier this year.

“With these activities, our hope is that everyone walks away learning something new,” he says. “Issues around data and security affect every business — from non-profits to large banks.”

With Jay Cao, manager of the TD Management Data and Analytics Lab, Keng is working to build up computing resources at the School. While there’s a lot of work ahead, he is optimistic about what they can accomplish.

“We’re hoping to expand what we can do to help Rotman, other faculties and researchers across the University. We want to make sure that everyone has the knowledge and technology to complete modern data analysis.”

Written by Rebecca Cheung