Adi Steif

Dr. Adi Steif’s research is focused on developing and applying computational methods for high-throughput genomics, with a particular interest in characterizing disease mechanisms and evolution in the context of cancer. New measurement technologies are enabling large-scale genetic, transcriptomic and epigenetic profiling of tissues at the single cell level. Working alongside experimental collaborators, Dr. Steif uses statistical machine learning approaches to derive biological insights from these high-dimensional datasets in the presence of noise and measurement bias. Her past research contributions focused on copy number inference and clonal evolution in breast cancer, and characterizing changes in normal mammary tissue in the context of ageing and inherited cancer susceptibility.

Dr. Steif was previously a Junior Research Fellow at Trinity College, University of Cambridge and a member of the inaugural class of Schmidt Science Fellows. She completed her postdoctoral research at the Cancer Research UK Cambridge Institute and European Bioinformatics Institute with Dr. John Marioni. Prior to this, she obtained her Ph.D. at UBC and BC Cancer under the supervision of Dr. Sohrab Shah and Dr. Sam Aparicio.