Hugo Latourelle-Vigeant, Computer Science and Mathematics 2018, is a doctoral student studying Statistics and Data Science at Yale University.

Latourelle-Vigeant said when he started at Champlain Saint-Lambert, he knew next to nothing about computer science beyond an initial spark of interest.

“I never coded before or anything like that,” he said. “I went into it and I evidently really liked it given what I do now.”

Having completed high school in Quebec City, Latourelle-Vigeant moved to Montreal knowing no one, but said he was able to quickly make friends in his program.

“You get to have all your classes with the same people and I really liked that. The camaraderie developed because it was a small program and we all got to know each other. I considered all of them my friends.”

Latourelle-Vigeant said he was set on attending an English college where he could improve his language skills.

“I really learned my English while doing Cegep,” he said. “I fondly remember those years.”

After completing a Bachelor’s in Mathematics and Computer Science and a Master’s in Mathematics and Statistics, both from McGill University, Latourelle-Vigeant started eyeing ivy league schools in the U.S. for his doctoral degree.

“That was the reason I wanted to do my studies in English, it opened so many doors for me when I left McGill. I could apply more broadly all around the world.”

When he received word that he had been accepted to Yale for 2024, he was thrilled.

“I think you have to really enjoy school to do a PhD,” he said. “It’s a very cool dynamic here. Everyone is really interested in learning in general. I’m fortunate to have the opportunity to be taught by people who really like what they teach.”

Latourelle-Vigeant’s research interest relates to machine learning models like ChatGPT, understanding exactly how they work and how they can be improved.

“With machine leaning, in practice we have developed these amazing models. But the thing is, we don’t really understand part of why they work or why sometimes they don’t work. So the research in machine learning theory that I am a part of is trying to understand how everything works,” he explained.

“It’s undeniable that these models are going to be part of our lives so I think it’s good to have some research into how we can make them better,” he said.

Hugo Latourelle-Vigeant’s advice for current students and recent grads: “It’s much better to try something and to fail or be rejected than to not try it and look back and regret. Try things and get out of your comfort zone. All of the best things that happened to me were from taking a risk. The things you remember down the line are not the times you tried and it didn’t work, you remember the times you succeeded.”