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Irene Melgarejo Lermas has never been one to shy away from a challenge. At the recommendation of a friend who studied at ��ݮ��Ƶ, she moved from her native Spain to study quantum field theory at the Institute for Quantum Computing (IQC). In addition to tackling a complex subject in her second language, she was assigned to teach a class of 200 undergraduate students during her first semester. “I didn’t have any teaching experience at the time,” she remembers.

Irene persevered through a difficult start and enrolled in the University’s Fundamentals of Teaching program, which significantly increased her comfort level in the classroom. The communications training she received throughout the program also propelled her to win the Faculty of Mathematics heat of the Three-Minute Thesis (3MT) competition. In her winning bid to condense her research into a one-slide, three-minute presentation, Irene employed a puzzle analogy. "Quantum field theory explores the intersection of quantum mechanics and the theory of relativity,” she explained. “The problem is that the detectors we use to study the quantum field can only give us scrambled information about a small part of a field, like a random handful of puzzle pieces. To overcome this problem, we use machine learning to unscramble this information and see where these few pieces fit, allowing us to see the bigger picture.”

As she reflects on time at ��ݮ��Ƶ, Irene points to the mental challenge of conducting research in a rapidly evolving field. “I’ve had to overcome the fear of failure,” she admits. “It’s easy to become paralyzed when something doesn’t work the way you expect.” In her lowest moments, she relies on support from her friends and classmates in Applied Math and IQC. “I’ve learned to ask for help when I need it,” she says. “There are so many opportunities to collaborate, and I’ve made some of my closest friends in the process.”

As she completes her thesis, Irene has her sights set on a graduate degree in data analysis and artificial intelligence at ��ݮ��Ƶ. “I plan to continue focusing on machine learning now that I’ve seen its practical applications,” she shares. “��ݮ��Ƶ provides an ideal environment to study quantum computing. This is where new ideas begin.”