The federal government’s Canada Research Chairs program invests up to $311 million per year to attract and retain some of the world’s most accomplished and promising minds. Chairholders are recognized to be national and international experts in the fields of engineering and the natural sciences, health sciences, humanities and social sciences. Brock University has 11 active Canada Research Chairs, with more to be announced. This monthly series profiles the work, and lives, of Brock’s Chairholders.

Growing up in the countryside of China, Yifeng Li frequently played with the family’s dogs and cats. He often sought solace from his pets, especially after his grandmother’s sudden death from cardiovascular disease.

Li had already lost his grandfather, who died of cancer before he was born.

“These early childhood experiences inspired me to pursue knowledge and wisdom with the faith of goodness, and eventually become a researcher for the betterment of our community,” says Li.

Fast forward several decades and the Assistant Professor of Computer Science and Biological Sciences has channeled his love of mathematics into designing medicines that treat diseases like those that took his grandparents.

Li’s work as Canada Research Chair in Machine Learning for Biomedical Data Science involves bioinformatics, an emerging area of study in which software tools and methods are used to reveal patterns embedded in complex, large biological data sets.

His research focuses largely on harnessing artificial intelligence (AI) and machine learning to develop, or refine, drugs to treat cancer, diabetes and Alzheimer’s, among other conditions, and reduce the drugs’ negative side effects.

An appreciation for the mathematical precision that goes into these designs is central to Li’s personality and career journey.

Throughout his education, which includes a master’s in Computer Science from the Qilu University of Technology in China, he loved the elegance of how mathematics explained everything in minute detail. Even while pursuing his PhD in computer science at the University of Windsor, Li was drawn to mathematics.

“The computer science department was on the eighth floor,” he says. “I would often walk up to the math department at the ninth and 10th floor to attend seminars and audit graduate courses, as I found computer science and math researchers are often doing similar work but lack communications.”

Li’s observation of mathematics’ pivotal role in computer science made him creative in applying his math knowledge and skills in several areas of study beyond computer science.

One of these areas was the field of computational biology, a multidisciplinary intersection of computing, mathematics and life sciences.

Objects such as microscopic cells, DNA and proteins found in raw medical images and biological samples have complex relationships not easily discernible through human means alone, says Li.

Using sophisticated computer technology, he and his team create algorithms that separate out and group together biological objects.

The technology can then do a deep dive into how these groups of objects interact with one another, producing insights in an efficient, timely manner beyond the scope of human efforts, says Li.

“With biomedical images, for example, it would take too much time for humans to segment out cells from a big image,” says Li. “If you’re the person in the lab and are given 10,000 microscopic images, can you segment them all by hand?”

This information enables Li and his team to develop drugs that target specific biomarkers where disease is caused.

Li is passionate about advancing his research beyond the lab, particularly through building connections with others.

As a participant in the 2023 Science Meets Parliament event, he was excited to learn about federal government science policies and programs through his discussions with members of Parliament (MPs) and senators.

Also dear to Li’s heart is his role as a mentor.

“Training a student is multi-dimensional, and everyone is unique,” he says. “Not only do I teach students advanced professional skills, but I also guide them to learn how to learn, build their vision and understand the responsibility of applying technologies, and I tell them to take a break if they are tired.

“I’m interested in training students so that they can continue in a career. My previous postdoctoral supervisor said each student was like half his child, that his students were an essential part of his life; it’s the same with me, too.”