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When Niki Mehri started planning her graduate studies, she knew one thing for certain: she wanted to tackle complex problems in health care by engineering solutions, but needed the right skills to do it. 

“It was mostly about the skills that I wanted to gain,” says Mehri, BSc’25. 

Originally a kinesiology undergrad, Mehri was drawn to engineering because of its focus on practical problem solving, as well as its emphasis on real-world application. Now enrolled in the Master of Engineering (MEng) program at the University of Calgary’s , Mehri has transitioned to biomedical engineering. The accelerated, course-based format of the MEng has been a “huge game changer,” she says. 

Choosing an accelerated path 

Mehri’s first exposure to biomedical engineering came through her kinesiology honours-thesis research on applying low-level electric currents to the vestibular nerves of the inner-ear for improving balance and gait. 

One of the factors that drew Mehri to Schulich was the structure of its MEng program. Although the program is designed to be done in two years, Mehri plans to do it in less than one. "It's great knowing I can complete the program in two semesters," she says. 

Mehri approached the program with a clear intention: to gain practical, industry-ready skills and make every class count. 

"I gained experience designing machine-learning workflows and making sure everything was reproducible, well-documented and easy for interdisciplinary teams to work with," she says. 

These practices are essential in industry, where, Mehri says, "clear and interpretable documentation helps interdisciplinary teams collaborate, especially when people come from different technical backgrounds." 

Machine ‘unlearning’ provides a new path 

Mehri says she has been able to build on her previous kinesiology knowledge through her MEng coursework. “There’s a lot of skills that you can gain from this program and apply to different fields whether that be medicine, research or industry,” she says.  

Before starting the program, Mehri was looking for a way to expand on her technical skillset. 

"I've always wanted to work across multiple disciplines," she says. "Kinesiology gave me the foundational science, biomedical engineering taught me the techniques to turn ideas into real solutions, and now, I'm ready to use the technical tools I've learned during my MEng." 

That approach is already shaping her work. Mehri is currently involved in her next research project studying "machine unlearning," an emerging method that allows trained models to remove the influence of specific data. Machine unlearning is especially important in health care, where patients may request that data be removed.   

Through a collaboration with , Mehri is helping drive interdepartmental AI research in two labs overseen by , PhD, in the Department of Electrical and Software Engineering and , PhD, in the Department of Biomedical Engineering.

Mehri is advancing machine unlearning so that health-care models remain stable after the removal of specific patient data. 

"I'm excited to keep building on machine unlearning in the next stage of my studies," Mehri says. Her research recently earned the Best Poster award at the hosted by UCalgary. 

Growing into an engineer 

Beyond technical skills, Mehri says the experience has reshaped how she sees herself professionally. Through applied coursework and accelerated learning, she has built confidence in engineering concepts that once felt unfamiliar. 

For students considering graduate studies, especially those coming from non-engineering backgrounds, she says initiative matters. 

“That first hurdle of reaching out really makes a difference,” Mehri says. 

She says Schulich faculty members were supportive and informative when she reached out to discuss how the program could align with her goals.  

“The faculty are amazing," Mehri says. "They love to help students out and they love to get you involved in what they're doing.” 

Mehri is working towards designing optimized solutions for complex human-centred problems.   

She says biomedical engineering is evolving rapidly, driven in part by the growing availability of clinical data. 

“My interests lie in developing machine learning systems that can process complex biomedical data in ways that are interpretable, reliable and capable of real-world implementation,” says Mehri.   

Mehri hopes to continue to grow into an engineer. “After my MEng, I’ll be starting an MSc in electrical and computer engineering, and I’m excited to keep expanding on what it means to engineer solutions while growing into a researcher,” she says.