Michael Hoffman is a principal investigator at the Princess Margaret Cancer Centre and Assistant Professor in the Departments of Medical Biophysics and Computer Science, University of Toronto. He researches the application of machine learning techniques to epigenomic data. He previously led the National Institutes of Health to ENCODE Project's large-scale integration task group while at the University of Washington. He has a Ph.D. from the University of Cambridge, where he conducted computational genomics studies at the European Bioinformatics Institute. He also has a B.S. in Biochemistry and a B.A. in the Plan II Honors Program at The University of Texas at Austin. He was named a CIHR New Investigator and has received several awards for his academic work, including the NIH K99/R00 Pathway to Independence Award and the Ontario Early Researcher Award.
Research
We develop machine learning techniques to better understand chromatin biology. These models and algorithms transform high-dimensional functional genomics data into interpretable patterns and lead to new biological insight.
For more information please visit https://hoffmanlab.org