Mentorship and machine learning: Graduating student Irene Fang is a leader wherever she goes

June 15, 2023 by David Goldberg - A&S News

Majoring in human biology and immunology, Irene Fang capitalized on opportunities inside and outside the classroom to research innovative methods in ultrasound detection driven by artificial intelligence and machine learning. She’s also working on research into cells and proteins in humans that could lead to new treatments and therapies for immunocompromised patients.

As she earned her honours bachelor of science degree, Fang always wanted to help others succeed. As a senior academic peer advisor with Trinity College, she’s admired throughout the community for her brilliance, kindness and dedication to U of T.

“I want to keep giving back because I am so appreciative of the upper-year mentors I connected with, starting in first year,” says Fang. “They continue to serve as an inspiration, motivating me to further develop professional and personal skills.”

Why was U of T the right place for you to earn your undergraduate degree?

U of T provided a plethora of academic, research and experiential learning opportunities alongside a world-class faculty to help cultivate my curiosity and consolidate my knowledge. In conjunction with an unparalleled classroom experience, I gained a real-world perspective with international considerations through the Research Opportunities Program.

I would be remiss if I didn’t also mention how extracurricular activities enhanced and enriched my university experience. The many clubs at U of T helped me focus on my passions and make meaningful connections with like-minded peers who became my support network, enabling me to reach my full potential.

How do you explain your studies to people outside your field?

I’m interested in machine learning, which is an offshoot of artificial intelligence that teaches and trains machines to perform specific tasks and identify patterns through programming.

There are two types of machine learning. Supervised learning involves training your machine learning algorithm with labelled images. In unsupervised learning, your algorithm learns with unlabeled images; this is advantageous as it eliminates the need to look for expert annotators or sonographers to label the images, saving time and costs. My research project compared how well unsupervised learning was able to identify and classify the three distinct ultrasound scanning planes at the human knee with supervised learning, the current standard for machine learning in ultrasound images.

My research project in immunology seeks to explore how a particular protein or receptor expressed on a specific subpopulation of human memory B cells mediates their immune responses. This is significant as memory B cells generate and maintain immunological memory, eliciting a more rapid and robust immune response upon the re-exposure to the same foreign invader, such as a pathogen or toxin, enabling a more effective clearance of the infection.

How is your area of study going to improve the life of the average person?

It is absolutely fascinating that AI has already revolutionized the medical field. Specifically, AI possesses the potential to aid in the classification of ultrasound images, enhancing early detection and diagnosis of internal bleeding because of injuries or hemophilia. Overall, AI may lead to more efficient care for patients, thereby improving health outcomes.

In terms of my immunology research, since the memory B cells expressing the specific receptor are dysregulated in people suffering from some autoimmune disorders and infectious diseases, a better understanding of how memory B cells are regulated could provide valuable insight into the underlying mechanisms of such diseases so we can enable scientists to develop new therapies that alleviate patients’ symptoms.

What career or job will you pursue after graduation?

I aspire to pursue a career in the medical field, conduct more research and nurture my profound enthusiasm for science while interacting with a diverse group of people. I hope to devote my career to improving human health outcomes while engaging in knowledge translation to make science more accessible to everyone.

You spent time at U of T as an academic peer advisor. Why was this work so important to you and what made it so fulfilling?

I remember feeling overwhelmed as a first-year student until I reached out to my academic peer advisors. Had I not chatted with them, I would not have known about, let alone applied for, my first research program. Looking back, it opened the door to many more new, incredible possibilities and opportunities. This experience made me realize the significance and power of mentorship, inspiring me to become an academic peer advisor. Seeing my mentees thrive and achieve their goals has made this role so rewarding — so much so that I am determined to engage in mentorship throughout my career after graduation.

What advice do you have for current and incoming students to get the most out of their U of T experience?

Ask all questions because there are no silly questions. Get involved, whether it be volunteering, partaking in work-study programs, sports or joining a club. Meeting new people and talking to strangers can be daunting, but the undergraduate career is a journey of exploration, learning and growth.

Be open-minded and don’t be afraid to try something new. Immersing yourself in distinct fields enables you to discover your interests and passions, which can lead you to an unexpected but meaningful path.

Also, be kind to yourself because failures are a normal part of the learning process; what’s important is that you take it as an opportunity to learn, grow and bolster your resilience. And finally, although academia and work can keep you busy, remember to allocate time for self-care. Exercise, sleep and pursue hobbies because mental health is integral for success in life.

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