Xiaojian Shao (Ph.D)
Research Officer
Digital Technologies Research Centre
National Research Council Canada
Building M50 | 1200 Montreal Road, Ottawa, Ontario, Canada K1A 0R6
Phone: (613) 993-5210
Email: xiaojian.shao@nrc-cnrc.gc.ca
Adjunct Professor
Department of Biochemistry, Microbiology and Immunology
Faculty of Medicine, University of Ottawa
Ottawa, Ontario, Canada K1H 8M5
Email: xshao2@uottawa.ca
I was trained in applied mathematics, optimization and machine learning where I had spent several years on studying support vector machines. During my Ph.D training under the supervision of Prof. Naiyang Deng and Dr. Gary Bader, I started to gain expertise in computational biology and bioinformatics, and had developed machine leanring tools to quantitavely predict protein domain-pepetide interactions. After gratudation, I started a position at Beijing Institute of Genomics, Chinese Academy of Science, where I extent my research interests to the genomic/epigenomic field and had dedicated to decipher the DNA methylation patterns dynamics within cell-population. Later on, I joined McGill Genome Center as a postdoctoral fellow and subsequently research staff under the supervision of Dr. Tomi Pastinen, Dr. Elin Grundberg and Dr. Guillaume Bourque. During that peroid, I worked on developing computational methods for analyzing whole genome bisulfite sequencing and methylome capture sequencing data, looking at genetic and epigenetic impacts in human complex diseases.
I collaborate extensively with biologists and clinicians to investigate the genetic and environmental effects on human complex diseases including metabolic, immune, neurodegenerative diseases as well as reproductive diseases.
I have opportunities for Masters or Ph.D students to assist with various research projects related to AI in biological systems and computational epigonomics. These positions will be co-supervised with Canadian university professors. Please email me with transcripts and CV if interested.
Research Interests
- Bioinformatics | Computational Biology
- Epigenomics | Single Cell Genomics
- Machine Learning and Optimization | Data Science