About Me
Qingrun Zhang's Lab in Biostatistics & Health Data Science
Qingrun Zhang's Lab in Biostatistics & Health Data Science
I am an Assistant Professor in Biostatistics in the Department of Mathematics and Statistics in University of Calgary. I also have an adjunct appointment in the Department of Biochemistry and Molecular Biology, with membership in Arnie Charbonneau Cancer Institute and Alberta Children's Hospital Research Institute. I was trained in biotechnology (B.S. in Yunnan University) and statistical genetics (Ph.D. in Chinese Academic of Sciences, Beijing Institute of Genomics, supervisor: Dr. Jurg Ott). Before moving to Calgary, I have received my postdoctoral training in Gregor Mendel Institute and Icahn School of Medicine at Mount Sinai.
I am an Assistant Professor in Biostatistics in the Department of Mathematics and Statistics in University of Calgary. I also have an adjunct appointment in the Department of Biochemistry and Molecular Biology, with membership in Arnie Charbonneau Cancer Institute and Alberta Children's Hospital Research Institute. I was trained in biotechnology (B.S. in Yunnan University) and statistical genetics (Ph.D. in Chinese Academic of Sciences, Beijing Institute of Genomics, supervisor: Dr. Jurg Ott). Before moving to Calgary, I have received my postdoctoral training in Gregor Mendel Institute and Icahn School of Medicine at Mount Sinai.
Currently, I am leading a small research group to develop Machine Learning algorithms focusing on high-dimensional data, with applications to the integration of genomics and gene expression data to predict risk and occurrence of diseases, as well as drug responses. Collaborating with colleagues in the Cumming School of Medicine, we develop computational tools tailored to different diseases including cancers and neurodevelopment disorders. Our research addresses the following questions: (1) How to learn sensible representations of high dimensional data. (2) How to identify association and causality using data mining techniques for complex multi-scale data. (3) How to carry out statistical inference in noisy and biased data, in particular, single-cell sequencing data.
Currently, I am leading a small research group to develop Machine Learning algorithms focusing on high-dimensional data, with applications to the integration of genomics and gene expression data to predict risk and occurrence of diseases, as well as drug responses. Collaborating with colleagues in the Cumming School of Medicine, we develop computational tools tailored to different diseases including cancers and neurodevelopment disorders. Our research addresses the following questions: (1) How to learn sensible representations of high dimensional data. (2) How to identify association and causality using data mining techniques for complex multi-scale data. (3) How to carry out statistical inference in noisy and biased data, in particular, single-cell sequencing data.
I am currently recruiting PhD students from the Statistics/Biostatistics streams in the Math & Stat Department to conduct interdisciplinary research. Candidates who are interested in may send CV and transcripts to my email address qingrun dot zhang at ucalgary dot ca. Thank you!
I am currently recruiting PhD students from the Statistics/Biostatistics streams in the Math & Stat Department to conduct interdisciplinary research. Candidates who are interested in may send CV and transcripts to my email address qingrun dot zhang at ucalgary dot ca. Thank you!
