Trent University has published a short video interview featuring Nasim Dadgar, as part of its Program Spotlight series. In the video, Nasim reflects on her experience at Trent, her journey as an international student from Iran, and how her studies in Big Data Analytics helped shape the early thinking behind Winelts.
This feature is especially meaningful for us because it connects an important part of the Winelts story to the academic environment that helped inspire it.
A spotlight on the journey behind the idea
The video is not yet fully about Winelts itself. Rather, it focuses on Nasim’s academic path and how Trent University supported her growth in data analytics, AI, and software development.
Still, for us, it is an important moment. Winelts was shaped by real experiences, real study, and real questions about how data and technology can be used to solve meaningful learning problems. Seeing part of that story featured in Trent’s Program Spotlight series makes this release special.
What Nasim shared in the interview
In the interview, Nasim talks about how memorable it was to receive her acceptance and begin imagining her future at Trent.
“I remember that I show it to my mom and dad and I said that they accepted me. This is the picture of my university.”
She also speaks about the campus itself and how important that environment was for her as an international student:
“The snowy pictures, fall pictures and the river campus are really beautiful in different season. As an international student from Iran campus was really important for me because you get the energy from the campus itself.”
That emotional connection to place, belonging, and motivation is a big part of what makes educational journeys meaningful.
Why Trent stood out
Nasim explains that Trent was one of the first universities she saw offering strong coverage of the Big Data Analytics stream, and that she believed the program had the knowledge and expertise to help her grow alongside the evolution of AI.
“Trent was one of the first universities who covered the big data analytics stream.”
She also highlights the way the program connected technical learning with the broader development of artificial intelligence and data analysis:
“I actually saw that they knew how to teach me this process and flow of evolution of AI and data analysis together.”
This combination of technical depth and future-oriented thinking is exactly the kind of foundation that can influence builders, developers, and founders later on.