Each year, faculty members from CANSSI member universities can apply to CANSSI’s Graduate Student Enrichment Scholarships (GSES) program for funding to enhance and broaden the training experiences of their graduate students in statistical sciences.
GSES recipients are jointly supervised by a junior faculty member who acts as lead and a more experienced faculty member who acts as a co-supervisor or sponsor.
This year, the program will support three doctoral students, each of whom will receive up to $15,000 over a two-year period running from 2024 to 2026. We are proud to introduce our latest GSES scholarship recipients and their research activities.
Kevin Lam, University of British Columbia
Kevin Lam is a PhD student in the Department of Statistics at UBC. He will be jointly supervised by Assistant Professor Yongjin Park (lead), Professor Alexandre Bouchard-Côté (co-supervisor), and Assistant Professor Benjamin Bloem-Reddy (co-supervisor). His project, built on ongoing collaborations with BC Cancer researchers, will focus on research related to triple-negative breast cancer (TNBC), the form of breast cancer with the worst clinical outcomes. Using single-cell genomics data from patient-derived xenograft (PDX) mice, he will work on the design of a principled statistical modelling framework for time-series single-cell data that has undergone different perturbation sequences, as well as several other research questions.
Bingqing Li, University of Toronto
Bingqing Li is a PhD student in the Department of Statistical Sciences at the University of Toronto. She will be jointly supervised by Assistant Professor Xin Bing (lead) and Associate Professor Dehan Kong (co-supervisor). Her project will address the problem of classification, an important topic of statistical learning theory. High-dimensional latent factor models that have a low-dimensional, hidden structure will be formulated to guarantee successful statistical classification performance based on suitable projections of the high-dimensional data into a low-dimensional space. Bingqing will investigate several choices of such projections. The work has important applications to recent advances in immunology and cancer studies. The usefulness of the new techniques will be demonstrated via applications to data from immunology, neuroscience, economics, genomics and proteomics.
Mingchi Xu, McGill University
Mingchi Xu is a PhD student in biostatistics in the Department of Epidemiology, Biostatistics and Occupational Health at McGill University. He will receive comprehensive statistical training that integrates the expertise of Assistant Professor Qihuang Zhang (lead) in statistical genomics and of Professor Alexandra M. Schmidt (co-supervisor) in Bayesian spatial statistics. Additionally, Qihuang Zhang will guide Mingchi in the analysis of spatial transcriptomics data. Mingchi will apply this training to the analysis of the spatial distribution of biological objects in the brains and plaques of Alzheimer’s patients with a focus on advancing existing Bayesian spatial statistics methods by adapting them for spatial transcriptomics applications. The scholarship activities will enable him to participate in collaborative projects with neuroscientists and to gain experience in communicating statistical ideas to non-statisticians.
Learn More About the GSES Program
CANSSI’s GSES program provides up to $15,000 over two years to support co-supervised training experiences for master’s and doctoral students enrolled in statistical sciences at CANSSI member universities. Applications must be submitted by faculty members during the application period, which runs from September 15 to November 30 each year.
