Kaiqiong Zhao, currently a PhD candidate in the Department of Epidemiology, Biostatistics, and Occupational Health at McGill University, will be developing innovative analytical methods and statistical inferences for large quantitative medical imaging and genetic data in biomedical research when she begins her CANSSI Distinguished Postdoctoral Fellowship later this year. The goal is to help predict the time to onset of Alzheimer’s using multi-modality imaging and genetic data.
This research can substantially increase the ability of researchers to draw accurate, scientifically valid conclusions about Alzheimer’s mechanisms, helping patients to deal with the disease and improving the lives of hundreds of thousands of patients and families in Canada and beyond.
Kaiqiong’s PhD thesis is about developing statistical methods for analyzing whole-genome sequencing data for DNA methylation and is expected to be completed in July 2021. She obtained an M.Sc. in computational biology from the University of Manitoba and an M.Sc. in statistics from the University of Windsor. During her postdoc, Kaiqiong will work on the project Novel statistical modeling of neuroimaging and genetic data with an application to Alzheimer’s risk prediction under the supervision of Professor Linglong Kong, University of Alberta, and Professor Dehan Kong, University of Toronto.
“I am thrilled to have such an excellent opportunity to extend and deepen my scientific abilities,” says Kaiqiong. “I look forward to acquiring more in-depth knowledge in high-dimensional functional data analysis, sparse learning and robust statistics from both supervisors, and establish collaborative projects with researchers from both universities.”
About the Supervisors
Dehan Kong is currently an Assistant Professor in the Department of Mathematical and Computational Sciences at the University of Toronto Mississauga and the Department of Statistical Sciences at the University of Toronto. He is a recipient of the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Accelerator Supplements Award. Currently, Dehan is serving as an associate editor for the Canadian Journal of Statistics and an editorial board reviewer for the Journal of Machine Learning Research. His main research area focuses on neuroimaging data analysis, statistical machine learning, functional data analysis, statistical genetics, and causal inference.
Linglong Kong is an Associate Professor at the Department of Mathematical and Statistical Sciences of the University of Alberta and a Canadian Research Chair in Statistical Learning. He has published more than 50 peer-reviewed manuscripts including top journals AOS, JASA and JRSSB, and top conferences ICML, ICDM, AAAI and IJCAI. Currently, Linglong is serving as associate editors of Journal of the American Statistical Association, International Journal of Imaging Systems and Technology, Canadian Journal of Statistics, member of the Board of Directors of the Statistics Society of Canada and Western North American Region of The International Biometric Society, the ASA Statistical Imaging Session program chair-past and the ASA Statistical Computing Session program chair-elect. His research interests include statistical machine learning, high-dimensional data analysis, neuroimaging data analysis, robust statistics and quantile regression.
CANSSI’s Distinguished Postdoctoral Fellowships
This program provides a comprehensive training experience to prepare postdoctoral fellows for success in a variety of careers. The CANSSI Distinguished Postdoctoral Fellowship will include a substantial research project in statistics or inferential data science, a substantial interdisciplinary or applied collaboration/interaction, teaching experience, broadly defined, equivalent to 1-2 courses total over two years, and opportunities for professional development. This two-year fellowship is supported by a competitive salary.