Dr. Emad is an Assistant Professor at the Department of Electrical and Computer Engineering at McGill University. He is also affiliated with the McGill initiative in Computational Medicine (MiCM), the Quantitative Life Sciences (QLS) program and Meakins-Christie Laboratories at McGill University as well as with the National Center for Supercomputing Applications (NCSA) at the University of Illinois (UIUC). In addition, he is an associate member of the Quebec AI Institute, MILA. 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 (UofA) in 2009 and his BSc from Sharif University of Technology (SUT) in 2007, all in Electrical and Computer Engineering.
Dr. Emad is the recipient of various awards including the NSERC Postdoctoral fellowship (2015), the UIUC CompGen Graduate Fellowship (2014), the UIUC Sundaram Seshu Summer Fellowship (2012), the NSERC Alexander Graham Bell Canada Graduate Scholarship (2010), the NSERC M.Sc. Postgraduate Scholarship (2008), the iCORE Graduate Student Scholarship in ICT (2008), the UofA Graduate Student Scholarship (2008), the UofA Walter H. Johns Graduate Fellowship (2008), the SUT Exceptional Qualification Award (2003) and the gold medal in Iran’s national Physics Olympiad (2003).
Antoine received his PhD from McGill University in Computational Biology. His current research interests are focused on developing deep learning algorithms for prediction of response of cancer patients to immunotherapies and for prediction of response to drug combinations in cancer.
David earned his Master’s degree from Korea Advanced Institute of Science and Technology (KAIST) in Electrical Engineering and his Bachelor’s degree from the University of the Philippines - Diliman in Computer Science. He is the recipient of the prestigious McGill MEDA award. His research interests include machine learning and graph mining in pharmacogenomics. Currently, he is developing novel computational models to predict the drug response and identify therapeutic targets in cancers and respiratory diseases such as cystic fibrosis.
Jointly supervised by Prof. Gregory Fonseca
Co-supervised by Prof. Hamed Najafabadi. Ali received his Master’s degree from Sharif University of Technology (Iran) in Computer Engineering and Artificial Intelligence. He has received the prestigious MEDA award at McGill. His research is focused on understanding the mechanisms of RNA splicing using deep learning models.
Joseph has spent the last 7 years studying cancer biology from both computational and experimental perspectives. These studies were conducted as part of his Master’s Degree in Experimental Medicine and Bachelor’s Degree in Biochemistry, both granted by McGill University. For the period between those degrees, Joseph was employed as a Machine Learning Developer at Coveo Solutions. He is the recipient of the prestigious Les Vadasz Doctoral Fellowships in Engineering. His research interests include creating computational tools for the analysis of single-cell omics data, particularly as applied to the context of cancers.
Jointly supervised by Prof. Mark Coates
Chen received her Bachelor’s degree from Dalhousie University (Canada) in Computer Engineering. Her research interests include computational regulatory genomics and machine learning. Currently, she is developing novel machine learning tools to reconstruct lineage-relevant transcriptional regulatory networks in human embryogenesis and COVID19-relevant regulatory networks.