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Aaron Petkau is a bioinformatician working for the Public Health Agency of Canada’s National Microbiology Laboratory and the current Head of Bioinformatics Pipeline Development within the Bioinformatics unit of the laboratory. His work primarily focuses on the development of bioinformatics software for infectious disease genomics. Some of his projects have included: developing tools for comparative genomics (GView and GView Server), phylogenetic analysis of microbial genomes (SNVPhyl), the management of genomics data (IRIDA), and indexing, querying, and visualization of mutations or genes derived from collections of microbial genomes (Genomics Data Index). He is currently focused on the development and integration of a diverse set of bioinformatics pipelines into a larger system for routine use within the Public Health Agency of Canada.
Her research is focused on understanding intratumoral heterogeneity, tumor evolution, and the tumor microenvironment at single cell resolution. She uses computational approaches to analyze, integrate, and interpret large-scale genomic data, with an emphasis on single-cell RNA-sequencing data. She completed a PhD in Genetics in the laboratory of George Church at Harvard Medical School, and a postdoctoral fellowship in Systems Biology with David Botstein at Princeton University. She was Research Faculty under the mentorship of Tim Ley at Washington University and the McDonnell Genome Institute.
Alysha Cooper is a current PhD candidate in Applied Statistics at the University of Guelph, with her research focusing on optimization of multivariate count outcome models for gut microbiome analyses. Before pursuing her doctoral studies, she gained valuable experience as a data analyst at the Homewood Research Institute in Guelph, ON. Alysha continues to work within the field of mental health and addictions as a part-time data analyst at the Peter Boris Center for Addictions Research in Hamilton, ON.
I conduct interdisciplinary research that integrates techniques and methods from machine learning, human computer interaction, and data visualization. I analyze data, build tools, and conduct evaluative studies. My research focuses on the intersection of Data Science and Data Visualization. I am especially interested in the way humans can collaboratively work together with ML/AI systems through visual interfaces. I completed my PhD in Computer Science at the University of British Columbia, where I was jointly advised by Tamara Munzner and Jennifer Gardy. Prior to my PhD, I was a research scientist at the British Columbia Centre for Disease Control and Decipher Biosciences, where I conducted research machine learning and data visualization research toward applications in infectious disease and cancer genomics.  My research has appeared in publications of the ACM (CHI), IEEE (TVCG, CG&A), Oxford Bioinformatics, and Nature.
Dr. McArthur is a Professor and David Braley Chair in Computational Biology at McMaster University and has had a career in the United States and Canada, including NIH-funded positions at the Marine Biological Laboratory and Brown University, where he led the genome assembly of the diarrheal pathogen Giardia intestinalis, plus 10 years of experience in the private sector. Dr. McArthur’s research team focuses on building tools, databases, and algorithms for the genomic surveillance of infectious pathogens. He and his team developed the Comprehensive Antibiotic Resistance Database (card.mcmaster.ca) and the SARS-CoV-2 Illumina GeNome Assembly Line software platform.
Andrew McPherson is an Assistant Laboratory Member at the Memorial Sloan Kettering Cancer Center in the Department of Epidemiology and Biostatistics under the supervision of Dr. Sohrab Shah. Andrew completed a PhD in computing science at Simon Fraser University under the supervision of Dr. Cenk Sahinalp and Dr. Sohrab Shah, focusing on methods for sequencing analysis, including detection and characterization of genome rearrangements, and inference of clonal phylogenies. During his post-doctoral research at University of British Columbia with Dr. Sohrab Shah, Andrew focused on the development of computational methods and infrastructure for a novel single cell sequencing plaform, Direct Library Preparation. Andrew moved to MSKCC in May of 2019 and plans to build on his post-doctoral work in single cell genomics to understand genomic instability, mutational processes, clonal evolution and the role of the microenvironment in cancer development and progression.
Dr Goldenberg is a Senior Scientist in Genetics and Genome Biology program at SickKids Research Institute, recently appointed as the first Varma Family Chair in Biomedical Informatics and Artificial Intelligence. She is also an Associate Professor in the Department of Computer Science at the University of Toronto, faculty member and an Associate Research Director, Health at Vector Institute and a fellow at the Canadian Institute for Advanced Research (CIFAR), Child and Brain Development group. Dr Goldenberg trained in machine learning at Carnegie Mellon University, with a post-doctoral focus in computational biology and medicine. The current focus of her lab is on developing machine learning methods that capture heterogeneity and identify disease mechanisms in complex human diseases as well as developing risk prediction and early warning clinical systems. Dr Goldenberg is a recipient of the Early Researcher Award from the Ministry of Research and Innovation and a Canada Research Chair in Computational Medicine. She is strongly committed to creating responsible AI to benefit patients across a variety of conditions.
Arnaud Droit is a full professor in bioinformatics in the Faculty of Medicine of Laval University. He is the director of the bioinformatics and proteomics platforms of the Research Center of the CHU de Québec – Université Laval. His laboratory focuses on the development of tools dedicated to the analysis of omics-type massive data, including genomics, transcriptomics, proteomics and metabolomics. His work provides a better understanding of the complex biological mechanisms of different diseases or biological phenomena. His team develops various approaches to identify multi-omics signatures using multivariate-driven methods such as machine learning and knowledge-based methods such as interaction networks.
Audrey is an M.Sc. student in the lab of Dr. Guillaume Bourque, in the Department of Human Genetics at McGill. She specializes in bioinformatics, more specifically on how genomic architecture and transcription are interrelated.
Dr. Benjamin Haibe-Kains is a Senior Scientist at the Princess Margaret Cancer Centre (PM), University Health Network, and Professor in the Medical Biophysics Department of the University of Toronto. Dr. Haibe-Kains earned his PhD in Bioinformatics at the Université Libre de Bruxelles (Belgium). Supported by a Fulbright Award, he did his postdoctoral fellowship at the Dana-Farber Cancer Institute and Harvard School of Public Health (USA). He is now the Canada Research Chair in Computational Pharmacogenomics and the Scientific Director of the Cancer Digital Intelligence Program at PM. Dr. Haibe-Kains’ research focuses on the integration of high-throughput data from various sources to simultaneously analyze multiple facets of carcinogenesis. Dr. Haibe-Kains’ team analyzes large-scale radiological and (pharmaco)genomic datasets to develop new prognostic and predictive models to improve cancer care.
University of Munich School of Medicine (1978-1985); Max-Planck Institute for Biochemistry (1985-1994); Gene Center of the University of Munich (1995-2001); University of Toronto (since 2001). I wish to understand complexity in adaptive systems. Complexity arises from the context dependent behaviour of system components, and in biochemistry we observe it in the hierarchies of structure formation, and the generation of function, across molecular, cellular and organismal scales. Recent scholarly work (since 2017, with Yi CHEN) has focussed on complexity in human relationality, ethics and aesthetics. Most recently (2022) I have founded the “Sentient Syllabus Project” as an international, public-good collaborative to address how academia can re-imagine itself in the face of our new wave of Artificial Intelligence capabilities. My teaching focuses on inquiry.