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Jeff Chen says he's always prioritized his academics, but what really elevated his performance to the next level was pouring his energies into the process of learning and self-improvement – rather than obsessing over the outcome.

“In my first year, I spent a lot of time anticipating the marks I would need to get a 4.0 GPA,” says Chen. “I stopped doing that in second year and cared more about the effort I put in to get the result.”

The approach bore fruit. Chen graduated this June with his bachelor of applied science in civil engineering, achieving 100 per cent in 17 of his 46 courses for an overall average of 96.5 per cent – the highest among his cohort of graduates across �鶹��Ƶ’s three campuses.

His performance earned him the 2024 , which is awarded annually to the top student from an undergraduate degree program at �鶹��Ƶ. His stellar academic record also led to him receiving a .

“This honestly wasn’t something I was expecting but I am immensely grateful,” says Chen. “I am treating these awards as a culmination of four years of hard work.”    

Chen adopted a methodical process to course work, starting his mornings by writing a list of what he wanted to accomplish that day. The items would be small, such as studying lecture notes for 15-minute increments, and he preferred to spread assignments and projects across several days. “I found that breaking things up helped me not get distracted and everything was continually fresh in my mind,” he says.

Chen also applied the same approach to his pastimes, which include playing chess, hiking and working out. “My hobbies allow for me to set and fulfill goals in the same way I approach my academics,” he says. “I’ve recently gotten into powerlifting, and I always aim to hit higher weights for the squat, bench and deadlift.” 

One of the highlights of Chen’s undergraduate career at �鶹��Ƶ was his fourth-year thesis, which explored the use of deep neural networks – a form of artificial intelligence – to predict the behaviour of structures during earthquakes.

The research focused on the seismic response of structural systems that exhibit non-linear stress-strain behaviour when subjected to strong forces. “Under an earthquake, dynamic forces on the structure are often strong enough that they enter this non-linear range, which has complex, difficult-to-predict behaviour,” Chen says.

The work, supervised by Professor Oh-Sung Kwon of the department of civil and mineral engineering, began when Chen received an undergraduate summer research award from the Natural Sciences and Engineering Research Council of Canada (NSERC).  

“The thesis project was completely open-ended and self-directed, unlike my course work, where outcomes are determined by the professors,” Chen says.  “I got to explore the intersection between artificial intelligence and structural engineering, and how we can utilize deep neural networks to design better and more resilient structures in the case of disasters.  

“I really enjoyed the challenge of working on this research, so I spent a lot of time on it.” 

This fall, Chen will take on his next academic challenge as a law student at the University of California, Berkeley. He says he’s looking forward to gaining foundational legal knowledge during his first year of law school before committing to a specific area of law. “I am keeping my options open, but I know my engineering degree will be useful, especially if I go into intellectual property law, since working on patents can be very technical.” 

Reflecting on his time at �鶹��Ƶ, Chen says he hopes his experiences will inspire other students to enjoy the journey of higher learning.

“�鶹��Ƶ has opened many doors for me and there are many paths I can take going forward.”