Congratulations to Shalev Manor and Gengyang Chen, who have both won 2026 Jessie W. H. Zou Memorial Awards for Excellence in Undergraduate Research ($1000 each).
The award, created by Dr. Ming Li and his family in honour of his late wife Jessie Wenhui Zou, recognizes and supports outstanding research at the undergraduate level.
Shalev Manor
Manor is a fourth-year student in Applied Mathematics, who received the award in recognition of two pieces of undergraduate research. “In essence, my research has focused on measuring the properties of physical systems, such as the mass of an object, the rates at which cancerous tumours grow, and how a chemotherapeutic drug interacts with tumours of different sizes,” he explains. “Measuring these properties is often challenging since these systems are constantly changing, and the effects of different properties can get all jumbled together.”
The award recognizes his work on two projects. In the first, he studied a simplified system of cancer growth and chemotherapy treatment, and demonstrated how to disentangle and measure the system properties of tumours and chemotherapy drug interactions. The second project focused on reducing the computational costs of acquiring the measurements from the first projects.
“It feels great to win this award!” Manor says. “I am proud of the work I’ve done and honoured to receive the award.” Manor is particularly grateful to his parents for their support, as well as Dr. Mohammad Kohanel for his teaching and research mentorship. “I am thankful to so many of my university professors and schoolteachers who encouraged me to do better and helped me build my academic foundations through many challenges along the way,” he says, “and I am grateful to my friends who made me feel welcome at university and who pushed me to try my best.”
Gengyang Chen
Gengyang Chen is a fourth-year student in Applied Mathematics and Statistics. She received the award in recognition of her research that proposes a new method for automatically selecting multiple hyper-parameters simultaneously in statistical and machine learning models. “Many modern learning architectures require tuning several hyper-parameters, and this process is often based on repeated manual inspection or exhaustive search,” she explains. The method her team developed helps automate the selection of these hyper-parameters. “We demonstrated our approach on elastic nets, support vector machines, and neural networks. Beyond hyper-parameter selection, we also explored how the same framework can be applied to other data-analytic settings.”
“I feel thrilled and very honoured to receive this award,” she says. “It is a wonderful recognition of my undergraduate research experience and feels like a perfect gift for my bachelor’s graduation as well as a celebration of a new starting point in my academic journey.” She wants to thank her supervisors, mentors, family, and friends for their support and encouragement. “I am especially grateful to Professor Mu Zhu for his invaluable guidance and support on the research project that led to this award,” she says, “as well as his mentorship, advice, and encouragement regarding my academic planning over the past year.”