My research focuses on the integration of high-throughput data from various sources to simultaneously analyze multiple facets of carcinogenesis. In particular, my team is analyzing radiological and (pharmaco)genomic datasets to develop new prognostic and predictive models and to discover new therapeutic strategies with the aim to significantly improve disease management. My main scientific contributions include several prognostic gene signatures in breast cancer, subtype classification models for ovarian and breast cancers, genomic predictors of drug response in cancer cell lines, and radiomic prognostic models in head-and-neck cancers. My team is also working towards developing new ways to improve transparency and reproducibility in computational research. My laboratory maintains multiple public genomic datasets and provides open-source software packages that are freely available to the scientific community (bhklab.ca).

For a list of Dr. Haibe-Kains's publications, please visit PubMed, Scopus, Publons or ORCID.

• Scientific Lead, Data Science Program, Princess Margaret Cancer Center, University Health Network
• Scientific Lead, Radiomics Program of the Radiation Medicine Program (RMP), Princess Margaret Cancer Center, University Health Network
• Associate Professor, Department of Medical Biophysics, University of Toronto
• Adjunct Professor, Department of Computer Science, University of Toronto
• Faculty Associate, Ontario Institute of Cancer Research
• Faculty Affiliate, Vector Institute
• Tier 2 Canada Research Chair in Computational Pharmacogenomics

• Canada’s Research Leaders at UHN