Tell us a bit about yourself before you enrolled in the Visual Computing program at SFU.
I come from India. Before I enrolled at SFU, I did my undergrad in Computer Science Engineering specializing in Bioinformatics.
My motto in life is to live in the present and have a good work – life balance. I used to dabble in many extra-curricular activities during college, which helped me to focus in class. I acted in a few short films, wrote a few scripts, and learnt a lot about film making. I joined M.A.D (Make a Difference) to help their initiative to educate underprivileged children and make them stand on their own feet with big dreams. While teaching these children about career choices, my own thoughts about a future career took shape and I decided to move forward with my studies in visual computing.
What attracted you to the visual computing program?
Studying for my bachelor’s degree, I got very interested in Artificial Intelligence. I was fascinated about working on machines which could make autonomous decisions and perform better than humans. For my final year project, I worked on Targeted Style Transfer using Cycle GANs, and it was then that I knew that I wanted to learn more about this field and pursue my passion further.
SFU’s Visual Computing program provided the perfect opportunity and I was delighted when it opened up last year. The courses in the program matches my interests, and gives exposure to all the cutting edge technologies being used in the Industry. It was a perfect fit, so I had no choice but to apply and I couldn’t have been happier for that decision.
Why did you choose to come to Canada?
This visual computing program is one of a kind, its courses have been particularly tailored for those of us whose primary goal is to join the workforce and it closely monitors the Industry’s demands. SFU’s research in visual computing is renowned worldwide due to the amazing professors working here and that attracted me further to join the university.
Employment opportunities are abundant here in Canada, especially for machine learning jobs. We’ve already had a few employer recruiters who specializes in computer vision and work with Augmented/Virtual Reality, 3D mapping, etc. speak with our cohort and give demos. It was inspiring to see their passion and drive towards the cause.
Also, I fell in love with Metro Vancouver when I visited last year. It’s a very peaceful place, with friendly people and plenty of things to see.
What is the most important thing you have learned in the program so far?
The program is thoroughly engaging and fast paced. Working with numerous new technologies is thrilling and mind boggling at the same time. You need to be quick at grasping new knowledge and thorough while implementing it. We worked with deep learning, robotics, and SLAM as well as the basics of machine learning within our first semester. Throughout these new tasks, the most important thing I’ve learnt is that hard work always pays off and to push myself to achieve the goals I set for myself.
Why do you think this program is significant?
I believe this program will be beneficial for both students and industry. It’ll help the students who want to work in this area gain knowledge and expertise from the people who’ve worked in computer vision for years. And because this program works closely with the demands of the industry, the recruiters get the talent that they actually need from the workforce.
What types of jobs are you looking for? How does this program fit with your career goals?
We’re learning in detail about various branches of computer vision in this program. This is exactly the kind of exposure I needed before joining a specific industry. I’m interested in working in virtual reality (VR), but I want to keep an open mind and am looking forward to explore more areas of computer vision over this next semester.
What would you tell potential students looking at SFU’s Visual Computing program?
I’d like to remind them, to only choose this course if they’re really interested in computer vision. We learn things in depth here, and it might mean long hours and efforts being put into each assignment. You need to be able to understand the concepts perfectly before implementing them. Also, I would suggest to read up on a few topics for the first semester to be better prepared. You can look into machine learning, deep learning in python, ROS (Robotics) and SLAM.