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Dr. Gary Van Domselaar, Ph.D. (University of Alberta, 2003) is the Section Chief for Bioinformatics at the National Microbiology Laboratory in Winnipeg, Canada and Associate Professor in the Department of Medical Microbiology at the University of Manitoba. Dr. Van Domselaar’s lab develops methods and pipelines to understand, track, and control circulating infectious diseases in Canada and globally. His research and development activities span metagenomics, infectious disease genomic epidemiology, genomic surveillance, genome annotation, population structure analysis, and microbial genome-wide association studies.
Burger is a member of the Robert-Cedergren Centre for Bioinformatics and Genomics, teacher in graduate bioinformatics education programs, and full professor in Biochemistry at the Universite de Montreal.
Gregory Butler is Professor emeritus of Computer Science and Software Engineering at Concordia University, Montreal, Canada. He is a founder of the Centre for Structural and Functional Genomics at Concordia where he directs the development of the bioinformatics platform for large-scale fungal genomics projects. His research focuses on advanced IT for knowledge-based bioinformatics, including scientific data management, algorithms, text mining, ontologies and the semantic web. Dr Butler is a founding member of the Canadian Semantic Web Interest Group.
Dr. Schwartz is a Scientist at the Princess Margaret Cancer Centre and Assistant Professor in the Department of Medical Biophysics at the University of Toronto. He has developed several methodologies for mutation detection, data integration, and cellular population visualization to understand cancer heterogeneity and diverse responses to anti-cancer therapies. His current research involves integrating multi-omic information and leveraging single-cell resolution to identify underlying mechanisms of drug resistance in cancer.
Dr. Bourque’s research interests are in comparative and functional genomics with a special emphasis on applications of next-generation sequencing technologies. His lab develops advanced tools and scalable computational infrastructure to enable large-scale applied research projects.
Dr. Hamed Najafabadi obtained his PhD from McGill University in 2012, followed by a postdoctoral fellowship in University of Toronto. He joined McGill University as a faculty member in 2016, where he is now an Associate Professor of Human Genetics and holds a Canada Research Chair in Systems Biology of Gene Regulation. His lab develops data-driven computational methods to characterize the role of gene regulatory factors in determining cell identity and function, and combines them with patient omics data to uncover the basis for development and progression of cancer.
Herbert H. Tsang is a Professor of Computing Science and Mathematics at Trinity Western University, where he leads the Applied Research Lab. He is also adjunct professor at Simon Fraser University. Previously, he served as a project engineer and R&D engineer at MacDonald Dettwiler and Associates. Tsang holds M.S. in electrical engineering and PhD in computing science from Washington University in St. Louis and Simon Fraser University respectively. His research focused on computational intelligence with applications in bioinformatics, computational criminology, and mobile computing. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM). Tsang is also a registered Professional Engineer (P.Eng.) in the province of British Columbia, Canada. Dr. Tsang received the International E-Learning Association’s Mobile Learning Award in 2018 and the Canadian Network for Innovation in Education’s Excellent and Innovation – Partnership & Collaboration Award in 2019.
Dr. Hong Gu is a professor of statistics in the department of Mathematics and Statistics, Dalhousie University. After receiving her PhD in Statistics from the University of Hong Kong in 1999, she worked as a postdoc in University of Waterloo for two years, then moved to Dalhousie University in 2001. Her research interests include multivariate data analysis methods, model selection and inference, molecular phylogenetic models, statistical data mining and statistical methodology development for omics data.
Igor Jurisica, PhD, DSc is a Senior Scientist at Osteoarthritis Research Program, Division of Orthopedic Surgery, Schroeder Arthritis Institute and Data Science Discovery Centre for Chronic Diseases, Krembil Research Institute, Professor at University of Toronto and Visiting Scientist at IBM CAS. Since 2015 he has served as Chief Scientist at the Creative Destruction Lab, Rotman School of Management, and since 2021 he is a scientific director of the World Community Grid. His research focuses on integrative informatics and the representation, analysis and visualization of high-dimensional data to identify prognostic/predictive signatures, determine clinically relevant combination therapies, and develop accurate models of drug mechanism of action and disease-altered signaling cascades. He has published extensively on data mining, visualization and integrative computational biology, including multiple papers in Science, Nature, Nature Medicine, Nature Methods, J Clinical Oncology, J Clinical Investigations. He has been included in Thomson Reuters 2014, 2015 & 2016 lists of Highly Cited Researchers (http://highlycited.com), and The World’s Most Influential Scientific Minds: 2015 & 2014 Reports. In 2019, he has been included in the Top 100 AI Leaders in Drug Discovery and Advanced Healthcare list (Deep Knowledge Analytics, http://analytics.dkv.global). In 2023, he has been included in the Top 100 AI in Oncology leaders: https://platform.dkv.global/map/reports/ai-in-oncology-leaders/
Jacek Majewski, Professor of Human Genetics at McGill University, began his adventure in science as a wannabe physicist and, veering through a brief stint with electrical engineering, eventually found his way to biology. He received a PhD in Evolutionary Biology from Wesleyan University in Middletown CT, and followed his then fiancée to New York City for a post-doc in statistical genetics with Dr. Jurg Ott at the Rockefeller University. When genome sequencing happened, a background in quantitative sciences proved useful, resulting in his involvement in multiple genomics projects aimed at understanding basic biology, hereditary disease, and cancer. After many years of denial, he was recently forced to admit that epigenetics does indeed exist, which led to ongoing interest in functional epigenomics.
James Green (PhD Queen’s University, 2005) is a full professor in the Department of Systems and Computer Engineering at Carleton University. His research focuses on machine learning challenges in biomedical informatics, particularly in the presence of class imbalance and the prediction of rare events. Current research projects include the prediction of protein structure, function, and interaction; the use of supervised and semi-supervised machine learning for the identification of microRNA in unique species; unobtrusive and non-contact neonatal patient monitoring; and the acceleration of scientific computing.
Our research focuses on the development of new algorithms, methods and software for analyzing genome sequencing data.