The Institute of Applied Mathematics is pleased to announce that the 2026 Dr. Deepak Kaura Award in the Mathematics of Medicine has been awarded to Wanxin Li, in recognition of her highly interdisciplinary work to advance computational methods that address three important challenges in biomedical data. Wanxin is an IAM member and a PhD candidate in the UBC Department of Computer Science, advised by Khanh Dao Duc and Yongjin Park. 

The first challenge addressed in Wanxin’s research is biological heterogeneity, in which a diversity of cell shapes and measurement conditions obscures meaningful patterns. To handle this, she introduces DeCOr-MDS, which uses n-simplex geometry to detect outliers and correct pairwise distances in biological datasets, and investigates the Riemannian elastic metrics for cancer cell shape analysis, demonstrating superior group separation over standard linear metrics in osteosarcoma and breast-cancer datasets. The second challenge is fairness: observed data or predictive models can treat different patient groups inequitably. Wanxin develops OTTEHR, an optimal transport framework for transferring predictive models across patient populations in electronic health records; this method can also be used to quantify treatment disparities. She also extends fairness testing from classification to regression by using the Wasserstein projection distance as a statistically rigorous measure of unfairness in regression models. The third challenge is data quality, where self-reported health information can be inconsistent across time. She proposes reliability-score-based stratification and Bayesian adjustment methods to reconcile conflicting self-reported onset ages in longitudinal health surveys, improving both disease correlation structures and predictive performance in the Canadian Partnership for Tomorrow’s Health dataset.