Qihuang Zhang
Qihuang Zhang is an Assistant Professor of Epidemiology, Biostatistics, and Occupational Health (EBOH) at McGill University and leads the Statistical Genomics and Intelligence Learning Lab (StaGILL). His research focuses on developing statistical and machine learning methodologies to address challenges in genetics and genomics data. His recent research has centred around developing methods to process medical images, spatial omics, and single-cell RNA-seq data. Previously, he received his Ph.D. in Statistics from the University of Waterloo in 2020 and was a postdoctoral fellow at the University of Pennsylvania.
Prof. Zhang has experience in developing statistical methods and machine learning algorithms for data with missing values, high dimensions, measurement errors, and complex association structures. His methods are applied in processing bulk and single-cell RNA-seq, spatial transcriptomics and metabolomics to discover new insights into Alzheimer’s Disease, COVID-19, and cancer.
Biostatistics, Measurement error, Misclassification, Statistical genomics, Machine learning, Interpretable Artificial Intelligence