Dr. Geoffrey Liu is a senior scientist at the Princess
Margaret Cancer Centre; a professor of Medicine, Medical Biophysics,
Pharmacology, and Toxicology at the Institute of Medical Science at the
University of Toronto; and a professor of Epidemiology at the Dalla Lana School
of Public Health at the University of Toronto. He is also a member of the
Computational Biology and Medicine Program at Princess Margaret Cancer Centre.
He graduated sum laude from the University of Toronto medicine program, followed
by residencies at the University of Toronto and a fellowship at the Dana Farber
Harvard Cancer Center in Boston. His research interests include epidemiological
outcomes, database methods, novel analyses of high-dimensionality biologically
rich data, pharmacogenomic analyses of conventional and molecularly targeted
agents using primary human xenograft models, patient-reported outcomes in
pharmacogenomics, and knowledge translation of personalized medicine and
pharmacogenomic algorithms into clinical practice. A major area of his research is
the use of machine learning approaches for the analysis of symptoms and
toxicity of cancer and natural language approaches in large-scale electronic
health data analysis in cancer.
Dr. Geoffrey Liu is a senior scientist at the Princess
Margaret Cancer Centre; a professor of Medicine, Medical Biophysics,
Pharmacology, and Toxicology at the Institute of Medical Science at the
University of Toronto; and a professor of Epidemiology at the Dalla Lana School
of Public Health at the University of Toronto. He is also a member of the
Computational Biology and Medicine Program at Princess Margaret Cancer Centre.
He graduated sum laude from the University of Toronto medicine program, followed
by residencies at the University of Toronto and a fellowship at the Dana Farber
Harvard Cancer Center in Boston. His research interests include epidemiological
outcomes, database methods, novel analyses of high-dimensionality biologically
rich data, pharmacogenomic analyses of conventional and molecularly targeted
agents using primary human xenograft models, patient-reported outcomes in
pharmacogenomics, and knowledge translation of personalized medicine and
pharmacogenomic algorithms into clinical practice. A major area of his research is
the use of machine learning approaches for the analysis of symptoms and
toxicity of cancer and natural language approaches in large-scale electronic
health data analysis in cancer.