�ؿ�ζSM

Some might view mathematics as an abstract discipline, but Sean Fridkin sees it as way to understand the world and solve problems – and he’s getting an early start.

Fridkin recently crossed the stage in the �ؿ�ζSM’s Convocation Hall to receive his honours bachelor of science in mathematics with a specialist in computer science, completing his high school and undergraduate studies in a total of four years.

Born in Israel, Fridkin spent most of his childhood and formative years in Bradford West Gwillimbury, Ont., where he managed to complete high school in two years after qualifying for a gifted students’ program. 

He says he wanted to attend U of T because it’s the top university in Canada. “U of T has the best faculty by far,” he said, citing among his inspirations Emeritus and Nobel Prize winner Geoffrey Hinton, “and you have opportunities to learn and take a bunch of different courses. 

"It’s also a very prestigious program, so in terms of job prospects, it’s really good. Plus, the people are great ... it’s a great place to learn, grow and network.”

Fridkin spoke to U of T News about his interest in math and computer science, plans for the future and thoughts on how students can get the most out of their undergraduate years:

How did you become interested in mathematics and computer science?

I think math is about trying to understand the world. All around, you have things going on, things happening, and math is seeing the patterns and getting a deeper understanding for what’s going on. That’s always interested me. I think it interests most people – they just don’t know that it’s called math and there’s a language for it.

The way I did my math major is I took a bunch of courses in different fields, but the main thing that unifies them is they teach you to think about the world in different ways. You have classes about the closeness of objects, analysis, topology, you’ve got to think about different types of infinities … You expand the way in which you think, and that interested me more than any specific path within mathematics.

In terms of computer science, I really like numerical methods, where you try to approximate – given some data – and interpolate with models to predict real things. I find machine learning numerical methods really fun.

What was your approach to learning while at U of T?

The number one goal for me in university was to learn how to learn – and learn how to think about new things and discover new ways of thinking. That’s the thing U of T gave me. You get the opportunity to talk to lots of different people, lots of different perspectives and learn from professors who are very experienced in the field and often have a unique way of thinking about different problems.

Also, with the assignments, you have to push yourself and that’s what I enjoyed about it. It was a little different from high school, where an assignment might take you 30 minutes. Here, for some of the math classes, I would have to initially spend maybe a couple of days on one assignment. And I learned a lot from that. I think it’s going to impact me, not only as I go further in my career, but also in life.

What are your plans for your career and education going forward?

I’m looking for computer science roles. I want to learn from interesting people and work on interesting problems. That’s the main goal. I don’t have any specific field that I’m going for within computer science – just interesting problems and people who I know I’ll be able to learn from and who I admire and respect.

I really enjoy learning, but I think most learning can be done informally, on your own or with good people at a company. But certainly, if there’s something interesting that I want to learn more about and that I can’t do on my own, I would 100 per cent go back to school.

Long term, I want to transition to something in the machine learning world. 

What would be your advice to students starting university?

I think the actual coursework is secondary to what you do in university. You should learn how to approach new problems ... For me, since I was going into math and computer science, I read a little bit of math stuff and I mostly worked on brain teaser problems. That helped me much more than any domain knowledge in any of the fields.

As soon as you build that thought process in your head – as soon as that becomes your natural way of thinking – everything becomes so much easier.