What was your educational background and industrial experience before joining the MScAC program?
Before joining the MScAC program, I completed my undergrad at IIT Bhubaneswar in India, earning a bachelor of technology in computer science. My focus throughout was on computer science, especially AI.
After graduating, I worked for two years as a software engineer at Google. It was during that time that I realized I wanted to pursue my master’s, so I left my job and joined the MScAC program
Why did you apply to the MScAC program and choose the Artificial Intelligence concentration?
As I mentioned, I was already inclined toward AI and machine learning during my undergrad, and I had relevant work experience too. When I was exploring master’s programs, this one felt like the perfect fit for both my background and what I wanted to do next.
I didn’t want to leave behind my software engineering background, but I also wanted to explore research. The applied research opportunity that this program offers was exactly what I was looking for. That was a big reason I chose it.
Plus, I had family in Canada, which made the transition easier and gave me a support system here.
What was your internship experience like being in Toronto, North America’s third-largest tech hub?
Being in Toronto, a major tech hub, added a lot to the experience. I attended talks—especially the Vector Institute talks — that gave me ideas I actually implemented during my internship. So overall, it was a really enriching experience.
But to add to that, being in Toronto also gave me access to a lot of startup-related events and job fairs. Those were super helpful in learning about what different companies are doing and exploring potential opportunities.
It was a great way to stay connected with the broader tech ecosystem.
Describe your experience working at AMD for your applied research internship.
The internship experience was really great. I interned at AMD, and the project I worked on covered everything end-to-end—from the research side, like collecting datasets and designing the model, to the engineering side, where I interacted with clients, understood their needs, and brought the model all the way to the deployment phase.
What advice do you have for any aspiring MScAC students?
My biggest advice would be to take full advantage of all the resources available. One thing I started doing a bit late was reaching out to professors and exploring more classes. If I could do it again, I’d definitely connect with more professors and alumni earlier in the program.
Also, make sure to find a good academic supervisor for your internship. That made a huge difference for me—it was incredibly helpful throughout the internship period.
And don’t overlook the networking opportunities the program offers.
After completing the MScAC program, what and where are you off to next?
Right now, I’m working at Chubb as an AI Engineer, and it’s been a really good opportunity. I get to work on model training, fine-tuning, and even some reinforcement learning, along with handling the deployment side of things.
The project itself is great, and the team is amazing. So for now, I plan to stay at Chubb unless another exciting opportunity comes along.
This Q & A has been edited for length and clarity.
What was your educational background and industrial experience before joining the MScAC program?
I completed my bachelor’s in computer science and engineering from Vellore Institute of Technology in India. During my undergrad, I had the chance to explore a wide range of technologies, and that’s where I discovered my passion for improving user experience using AI.
Although I joined the MScAC program directly after undergrad, I did a few internships in machine learning and data science, and I also published a few papers. That combination of academic and practical experience helped me transition straight into the master’s program.
Why did you apply to the MScAC program and choose the Artificial Intelligence concentration?
During my undergrad, I explored both research and industrial applications, and I realized I didn’t want to do just pure academic research or just pure engineering—I wanted to do applied research. I was looking for a program that would let me combine both worlds. Out of all the programs I applied to, MScAC was the only one that offered the perfect blend of applied research and real-world application.
I also wanted to build a strong foothold in the Canadian job market, and the eight-month internship was the perfect way to get my foot in the door. Plus, the reputation of U of T as one of the top universities really helps you stand out in a competitive market. I’d also heard a lot about the amazing faculty and the kinds of courses offered, which made the program even more appealing.
What was your internship experience like being in Toronto, North America’s third-largest tech hub?
Being in Toronto and working in tech here is honestly the best! I kept getting emails and notifications about different events and talks happening around the city. As U of T students, we had full access to attend these events, which made it super easy to connect with industry leaders and like-minded people.
Networking was basically handed to you on a platter, you just had to be social enough to take advantage of it. That’s something I really appreciated. Because of this exposure, I was actually invited to be one of the main speakers at the Women in Tech conference this year. Being in a tech hub and working as an ML specialist at UHN really helped make that happen. It was a pretty fun experience!
Describe your experience working at Surgical Artificial Intelligence Research Academy (SARA) at UHN for your applied research internship.
I chose UHN because I wanted to contribute to something that could make a real impact, whether it’s in healthcare or industry. The project they offered was super interesting and had a lot of learning potential.
It was definitely a steep learning curve, diving into the medical field without any prior experience working with medical data. But it was so rewarding. I learned how to work with medical data, 3D modeling, and how to use generative AI for medical problem-solving.
One of the biggest takeaways was learning how to communicate technical ideas to non-technical people. I had to work closely with surgeons, even watching a few surgeries to understand the data and context I needed for my project. In the end, I built a platform to help with surgical planning — something surgeons could use before going into the OR. That was incredibly fulfilling.
The team I worked with was also amazing and super supportive, which made the whole experience even better.
What advice do you have for any aspiring MScAC students?
Honestly? First, know that imposter syndrome is completely normal. Some of my peers were incredibly accomplished, and even I went through it. But you’re not alone, everyone feels that way at some point. Don’t be intimidated by someone who seems better than you. Instead, learn from them, get inspired, and grow together.
Second, take full advantage of the courses and faculty. Sixteen months goes by in a flash. Choose courses that align with what you want to do in the future. Go for project-based courses, interact with professors, and build those connections.
And finally, make the most of the incredible MScAC team. If you ever have any issues or concerns, just reach out — they’re always there to help. That’s been my experience, and it made a huge difference.
I remember just a few months ago, students were super stressed about the internship process, asking us tons of questions. I’d been in their shoes too. But in the end, you get through it, you land your internship, and then you look back and laugh at how stressed you were.
After completing the MScAC program, what and where are you off to next?
I’ll be continuing with UHN, working on a variety of projects. One of them is especially close to my heart. I’m focused on developing an interactive 3D platform that allows surgeons to explore a patient’s anatomy and simulate surgeries before entering the OR. And from there, let’s see where it takes us.
This Q & A has been edited for length and clarity.
What was your educational background and industrial experience before joining the MScAC program?
Before joining the MScAC program, I completed my bachelor’s degree in electrical engineering in Colombia. As part of my undergraduate studies, I had the opportunity to explore two very different areas of electrical engineering through internships.
In my first internship, I worked at a consulting firm focused on electrical substation design. I really enjoyed the experience and learned a lot, but I also realized that I wanted to be the person creating the tools, not just using them.
For my second internship, I was fortunate to work with professors at my university, Universidad Pontificia Bolivariana, on a feasibility study. We analyzed the potential replacement of some of San Francisco’s trolleybus lines with battery electric vehicles. That experience sparked my interest in applied research and ultimately led me to apply to the MScAC program at the University of Toronto.
Why did you apply to the MScAC program and choose the Computer Science concentration?
After graduating, I knew I loved my field, but I wanted to be behind the innovation, to be the one designing and building technology, not just using it. I became interested in computer science, not necessarily AI, but more in learning how to code and build useful tools.
I started looking for master’s programs across the U.S. and Canada and found the MScAC program. It offered the perfect combination of academic learning and real-world application. That balance really aligned with what I was looking for: to gain knowledge and apply it to solve real-world problems.
While completing the program, I noticed that most internship opportunities, probably around 80%, were AI-focused. I was more interested in foundational computer science, and the MScAC partnerships team was incredibly helpful in finding an internship that matched my goals.
What was your internship experience like being in Toronto, North America’s third-largest tech hub?
Toronto is an incredible tech and AI hub, but during my time in the program, I realized my interests leaned more toward foundational computer science rather than AI. With the help of the partnerships team, I found an amazing opportunity at D-Wave Systems. The internship was a perfect fit — it sat at the intersection of electrical engineering and computer science.
My project involved designing an electromagnetic simulation toolchain using open-source technologies. It was an incredible experience. I explored a wide range of technologies, had great mentorship, and shaped my learning journey by diving into software engineering best practices. It was deeply rewarding.
Describe your experience working at D-Wave Systems for your applied research internship.
D-Wave was exceptional. It was my first experience in the tech industry, and I finally understood what people meant when they talked about company culture. Everyone was supportive, willing to help, and eager to share their knowledge.
I learned so much because I was surrounded by brilliant people in a collaborative environment. I even received a return offer, and I’m now working at D-Wave full-time!
What advice do you have for any aspiring MScAC students?
First, I want to say that being accepted into this program is a privilege. When I applied, we were told that only about 5% of applicants were accepted. So, if you’re admitted, embrace the opportunity fully.
That mindset made all the difference for me. The MScAC program fosters a strong community among students, professors, and staff. People come from diverse cultures, backgrounds, and areas of expertise — everyone has something to teach you. I made it a point to always be open to learning from others, and that made the experience incredibly rewarding.
After completing the MScAC program, what and where are you off to next?
After my internship, I joined D-Wave full-time as a backend software developer, which aligns perfectly with my original interests. I’m part of the team responsible for D-Wave’s web services, and I’m constantly learning from my mentors and teammates. It’s an environment filled with incredibly knowledgeable people, and I’m excited to keep growing both technically and professionally.
Outside of work, I’ve been diving into personal projects. One thing I loved about the MScAC program was how many courses included side projects. That rhythm of continuous learning really stuck with me. Now, I’m especially interested in accessibility and have been experimenting with building an app in that space. I’ve been exploring different technologies and learning through online platforms like Coursera and other free virtual courses.
Ultimately, I want to find a way to make a meaningful impact in the world. I know that sounds a bit holistic, but it’s something I genuinely care about. Accessibility is an area where I believe technology can make a real difference, and I’m excited to keep learning and building toward that goal.
This Q & A has been edited for length and clarity.
What was your educational background and industrial experience before joining the MScAC program?
I completed my bachelor’s degree with a major in artificial intelligence and machine learning and a minor in economics from Amity University, Mumbai. I was honoured with a gold medal for both my class and the overall university performance.
Before joining the MScAC program, I didn’t have full-time work experience, but I completed two internships. One was with a startup based in Australia, where I worked as a machine learning engineer. The other was with a startup in Surat, where I served as a software development engineer focusing on Web3 applications.
Why did you apply to the MScAC program and choose the Computer Science concentration?
I was especially drawn to the opportunity to engage with industry leaders over the eight-month internship, which I saw as a unique way to understand how research is conducted and applied in real-world industry settings — whether in products or services. That practical exposure, combined with the prestige of the University of Toronto and its reputation in AI, made the MScAC program a perfect fit for me.
I chose the computer science concentration because it offered more flexibility in course selection. There weren’t strict limitations on which courses I had to take, so I was able to explore subjects from the mathematics and statistics departments during my two terms.
What was your internship experience like being in Toronto, North America’s third-largest tech hub?
Living in downtown Toronto has been amazing, it’s a fast-paced environment with a vibrant startup scene. My office is in Mississauga, but I don’t commute daily, so I often visited the MScAC office. The MaRS building and the Schwartz-Reisman Innovation Campus are nearby. One day, while walking down the street, I even bumped into a few startup founders and had a great conversation with them.
Overall, it’s been a fantastic experience. Downtown is full of tech and finance professionals, and being surrounded by such brilliant minds is incredibly inspiring.
Describe your experience working at J-Squared Technologies for your applied research internship.
I interned as a Machine Learning Engineer at J-Squared Technologies, and it was a great experience — not just because of the technical work, but also because of the broader responsibilities I was given. Andrew, the president of the company, involved me in a strategic acquisition project. I led parts of the process, tested integrations, and communicated with both the partner company and clients.
So, it wasn’t just a tech role, it also involved partnerships and people skills, which made it a well-rounded and enriching experience.
What advice do you have for any aspiring MScAC students?
Try to be as extroverted as possible. That’s key to landing an internship or job. In a competitive market, strong communication and people skills can set you apart. Companies value those who can collaborate and lead.
And this communication isn’t just for industry professionals or recruiters, it’s also important with your peers, alumni, and the MScAC team. These are the people who will support you throughout the program and even after graduation.
After completing the MScAC program, what and where are you off to next?
Right now, I’m still with J-Squared Technologies. After my internship, they offered me a full-time role, and I’ve continued working with them. As I mentioned earlier, it’s a hybrid role where I’m not just doing engineering work — I’m also developing my people skills and gaining experience in areas like partnerships and strategy.
Looking ahead, I’m considering business school. I’m surrounded by leaders at J-Squared who have spent 10–12 years in consulting and management, and they’ve really inspired me to explore that path. So, that might be my next big adventure.
This Q & A has been edited for length and clarity.
What was your educational background and industrial experience before joining the MScAC program?
I completed my bachelor’s degree at the University of California, San Diego, with a focus on data science, which included a mix of mathematics and computer science.
In terms of industry experience, I had only a few internships before joining the MScAC program, mostly in the biotech sector. Even though those roles were in data science and software development, they were still somewhat relevant to what I wanted to pursue.
My data science background is part of what led me to choose the MScAC program.
Why did you apply to the MScAC program and choose the Computer Science concentration?
My original focus was on the MSc program at U of T because I really wanted to do research. But as an undergrad with limited exposure to the full research pipeline, I figured it might be a good idea to submit an application to MScAC as well — and I’m really glad I did.
What stood out to me about MScAC was its unique structure. You start with coursework and then move into a mandatory internship, which I found really appealing. That model played a big role in my decision to enrol. I joined in 2023, when the job market was pretty uncertain, so having a dedicated period to gain professional experience — even without a guaranteed return offer — was incredibly valuable. It gave me a solid foundation to start my career.
To add a bit more context, my background was originally in data science, but I chose the Computer Science concentration because I wanted to become more technical. I also wanted to build a strong foundation in research, especially since AI is such a hot field right now. To really work in AI, you need both a research mindset and an engineering mindset, and I wanted to develop both.
What was your internship experience like being in Toronto, North America’s third-largest tech hub?
I really like Toronto, it’s a vibrant city with a great cultural scene and a strong tech industry. There’s a mix of large international companies and smaller, tech-focused divisions within other industries.
I interned at Sanofi, which is a biopharma company, but their Toronto office is also a tech-focused innovation hub. That’s something I found really interesting, how companies in non-tech sectors are building strong tech presences here. And it’s not just Sanofi; a lot of companies are doing this.
Describe your experience working at Sanofi for your applied research internship.
At Sanofi, I got to meet a lot of interesting people. As someone early in my career, that exposure was incredibly helpful. The hub itself was fairly new, only about two years old when I joined, so I felt like I was growing alongside it. I received a lot of guidance from my managers, and because the team was still figuring things out, it was easier for me to contribute ideas and have a real impact. Overall, it was a fantastic experience.
Sanofi’s innovation hub is very research-focused, which made it a rare and valuable opportunity for a master’s student. I got deep exposure to the industry research environment, which isn’t always easy to find at this stage. I think the internships offered through MScAC, especially with partners like Sanofi, provide a really strong foundation for anyone looking to start a career in computational science, machine learning, or AI.
What advice do you have for any aspiring MScAC students?
My biggest advice is to take initiative. MScAC offers a lot of resources, and the team has been incredibly helpful throughout my journey — whether it was landing an internship, transitioning to full-time, or just figuring things out during classes.
But I’d also extend that advice beyond the program. Take initiative in networking, too. You’re part of U of T, and the computer science department has a strong reputation. Many alumni and researchers from the department are big names in the field, so leverage that. Reach out, connect, and keep that momentum going.
After completing the MScAC program, what and where are you off to next?
I definitely see myself continuing in research. Right now, it looks like I’ll be doing that in industry with Sanofi. While I didn’t receive a formal return offer, I was offered a flexible, open-ended contract to continue working with the team on research related to biomedicine and AI.
So for the near future, I see myself progressing in this field, whether it’s with Sanofi or elsewhere. And if the opportunity arises, I’d love to return to Sanofi as a full-time applied scientist.
This Q & A has been edited for length and clarity.
