Amin Emad is an Assistant Professor at the Department of Electrical and Computer Engineering at McGill University and is an Associate Member at Mila. He is also affiliated with the McGill initiative in Computational Medicine (MiCM) and the Quantitative Life Sciences (QLS) program at McGill University as well as with the National Center for Supercomputing Applications (NCSA) at the University of Illinois (UIUC). Before joining McGill, he was a Postdoctoral Research Associate at the NIH KnowEnG Center of Excellence in Big Data Computing associated with the Department of Computer Science and the Institute for Genomic Biology (IGB) at UIUC. He received his PhD from UIUC in 2015, his MSc from the University of Alberta in 2009 and his BSc from Sharif University of Technology in 2007, all in Electrical and Computer Engineering.
Dr. Emad’s research is focused on the application of machine learning (e.g. deep learning, machine learning on graphs, etc.) in bioinformatics and computational biology. Particularly, he and his team develop novel computational tools to address various challenges in biology and medicine. These include problems such as prediction of drug response using ‘omic’ molecular profiles of patients, identification of biomarkers of drug sensitivity (e.g. in cancer, in kidney diseases, in chronic lung diseases, etc.), identification of disease subtypes to improve patient diagnosis, and deciphering the gene regulatory mechanisms associated with a phenotype. His other areas of interest include interpretable machine learning, machine learning for communication systems, graph mining, sparse inverse problems, and group testing.