UofT Statistical Sciences: Is there anything about your journey that you're proud of?
Nayan Saxena: When I first came here, I had a very rough experience at university, I did not have the best GPA, and I even dropped introductory statistics. I also did not qualify for the CS program which really brought my morale down. Given that, what I am the proudest of is how far I have come and everything I have accomplished to make the most out of my undergraduate experience.
Over the last few years, I have been able to publish several papers across various domains and have also been a teaching assistant for statistics courses at both graduate and undergraduate levels. I have collaborated with several people within Canada and abroad on projects with real-world implications, which has really broadened my perspective. More recently, I was selected by The Association for Computing Machinery (ACM), the Norwegian Academy of Science and Letters (DNVA), and the International Mathematical Union (IMU) as one of only 100 young researchers in the field of Computer Science from around the world to attend the prestigious 9th Heidelberg Laureate Forum.
Can you tell us more about some of the challenges you had to overcome?
In my first semester, I moved here from Bhopal which is a relatively small Indian city. When I came here, everything was intimidating, and I was just blown away. For instance, my focus would deviate toward the size of the library instead of being able to study within it. It is just little things like that, combined with being away from family, which really impacted my grades in my initial semesters.
Even talking in English was a bit of a hurdle for me. Initially, while I could hold a conversation in English, it was a challenge for me to engage in scientific discourse. The biggest challenge throughout for me was dealing with the sense of isolation that came with doing things that might not be what my peers were pursuing. For instance, I completed third-year statistics courses within my second year of study and went on to do fourth-year courses, including a graduate course in computer science, in my third year. This brought different challenges with it and made me question my goals and capabilities several times. By the time I was in my fourth year, I was already reviewing scientific papers for academic conferences—things like these made me lose touch with people from my actual cohort.
Is there anything you wish you knew before you started at U of T?
I would say it's important that you surround yourself with the right people, specifically people who make you feel valued. A lot of things are hedged against you as an international student. You are paying twice as much as domestic students. You don't have any family around, so your situation can be very different compared to a student who is commuting from home. Accepting the fact that everyone is dealt a different hand in life would have really helped me early on when I felt pressured to be a certain way. Every bad grade and every minor setback can feel like a massive failure when you are an international student. Creating value, for yourself and others, is what university is mostly about – and surrounding yourself with like-minded people really makes a difference.
What areas of research are you most interested in, and what work are you most proud of?
Throughout my undergraduate career, my primary goal has been to gain a better understanding of the underlying processes that govern intelligence across both humans and machines. That's why I have pursued several research projects ranging from deep learning to computational cognitive science. My primary objective is to solve practical challenges affecting deep learning approaches, while also finding ways to bridge the gap between industry applications and recent deep learning advances.
I am most proud of the projects that were completed independently, mostly without a supervisor or a graduate student, and then subsequently published or presented on a global scale. For example, I started an independent research collaboration with two of my friends last year from U of T. We have produced three papers so far on AI creating AI, also known as automated machine learning. We recently won scholarships to present our work at the 36th International Conference on Artificial Intelligence and have presented our work at research labs like the ML Collective and other conferences like the 38th International Conference on Machine Learning last year.
Tell me about a project you really enjoyed working on.
My favorite projects are often interdisciplinary. Recently, I collaborated with researchers from Nigeria to develop a 5,000 image pioneer dataset for Nigerian Sign Language which was then leveraged by statistical machine learning approaches to convert sign-to-speech in real-time. This work was featured in the Proceedings of the 31st International Joint Conference on Artificial Intelligence.
Also, statistical modeling approaches such as Gaussian Processes have played a central role in my work on understanding function learning in human beings supervised by Professor Daphna Buchsbaum from the Computational Cognition Lab at Brown University. Parts of this project were featured as a proceedings paper in the 19th International Conference on Cognitive Modeling and, more recently, subsequent iterations were presented as a poster at the 44th Annual Meeting of the Cognitive Science Society.
In what ways has your journey changed you as a person?
Compared to my first semester, I feel like a completely different person now. I certainly have become a better communicator over time and presented at various conferences. Aside from that, I would say I've become more confident and calmer. I stopped thinking of myself as a failure, and I'm more confident in my abilities and skills. This is partly because a common goal throughout my undergraduate studies was to come out of the setbacks I faced in my initial semesters and face each problem head-on. Life has changed for the better. In several ways, it has become the opposite of the beginning of my journey: from becoming a teaching assistant for the same introductory statistics course I dropped in my first semester, to doing graduate computer science courses after I didn't do well on introductory programming courses. It's been quite a transformative experience.
What do you think helped you get to a better place and pursue your goals and aspirations? What sort of advice would you give to a fellow student?
One key realization I had early on in my undergraduate studies, that helped me get to a better place, was that most people in my cohort, including me, will end up with an undergraduate degree — and I had to stand out. This meant making the most of my undergraduate studies.
I achieved this goal by working on meaningful projects as part of my courses. To a fellow student, I would say if you have a gut feeling that you can do something, just go for it. Even if you're uncomfortable, try to embrace failure and take risks. Students place a higher value on coursework than required. Contrary to popular advice, I would suggest that if there is something you feel can truly make a difference in your life, direct your efforts there.
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