People

Russ Greiner worked in both academic and industrial research before settling at the University of Alberta, where he is now a Professor in Computing Science (Adjunct in Psychiatry) and the founding Scientific Director of the Alberta Machine Intelligence Institute. He was elected a Fellow of the AAAI, was awarded a McCalla Professorship and a Killam Annual Professorship; received a 2020 FGSR Great Supervisor Award and in 2021, received the CAIAC Lifetime Achievement Award and became a CIFAR AI Chair. In 2022, he received the (UofA) Precision Health Innovator Award, then in 2023, he received the CS-Can | Info-Can Lifetime Achievement Award. For his mentoring, he received a 2020 FGSR Great Supervisor Award, then in 2023, the Killam Award for Excellence in Mentoring. He has published over 350 refereed papers, most in the areas of machine learning and recently medical informatics, including 6 that have been awarded Best Paper prizes.

Bioinformatician and data analyst in the Bader lab applying pathway and data analysis to varied data types. Developed Enrichment Map App for Cytoscape, an app to visually translate functional enrichment results from popular enrichment tools like GSEA to networks. Further developed the Enrichment Map Pipeline including development of additional Apps to help summarize and analyze resulting Enrichment Maps, including PostAnalysis, WordCloud, and AutoAnnotate App.

He graduated with Ph.D in Informatics from University of Missouri-Columbia in December 2019. His current work focusses on understanding Acute Myeloid Leukemia at the single cell level using Single cell RNA-sequencing analysis. He is interested in developing informatics approaches in Single cell RNA-seq to better understand Cancer.

I am currently the NGS sequencing core Manager/Research Investigator and member of the McCombie lab at Cold Spring Harbor Laboratory. I work in developing and adapting new technologies for Next-Generation sequencing routines and other applications. During my time here I have developed optimizations for the Pacific Biosciences RS instrument for large genome sequencing, evaluated rational pooling schemes for large cohort sequencing on Ilumina platforms, and I have developed applications for sequencing and error corrections on the Oxford Nanopore MinIon. Currently I am using optical mapping strategies to evaluation long structural variants in in cancer lines and Oxford Nanopore for CNV detection in clinical samples.

I am an Associate Professor at the Paul Allen School of Computer Science and Engineering at University of Washington (UW). Before joining UW, I was an Assistant Professor at the Department of Statistics and the Department of Medical Genetics at University of British Columbia (UBC), and a faculty member at the Vector Institute. I also held a Canada Research Chair (CRC II) in Computational Biology (2015-2020), and a Canada CIFAR Chair in Artificial Intelligence (CIFAR-AI). Before joining UBC, I did my postdoctoral fellowship with Daphne Koller at Stanford University. I got my PhD in Computer Science from the University of Toronto in 2011, working with Quaid Morris. My PhD thesis was on integrating large-scale genomics and proteomics datasets to predict gene function. Check out GeneMANIA to find out more about this project!

Sébastien Lemieux, an associate professor at the biochemistry and molecular medicine department of U. de Montréal and an associate academic member at Mila, has a robust background in both biology and computer science. As a principal investigator at IRIC, his work focuses on the development of deep learning models and bayesian frameworks for drug discovery, cancer prognostic, -omics data integration with applications in acute myeloid leukemia and targeted immunotherapy. His interdisciplinary approach showcases his dedication to advancing the field of bioinformatics through a variety of data sources, technical methodologies, and applications.

Sejin is a PhD Candidate at the University of Toronto working on applying deep learning models for personalized prognostication of head and neck cancer patients. As the lead developer of Med-ImageTools, an open-source Python package for processing medical images, he is determined to make sure his research is easily reproducible and accessible for the wider scientific community to increase clinical adoption of machine learning methods and ultimately improve patient outcomes.

Postdoctoral Fellow, UofT/UHN Senior Data Scientist, Pathomics.io Director, Panoramics – A Vision Dr. Shamini Ayyadhury is a computational postdoctoral fellow at the University of Toronto and University Health Network, applying and developing various computational pipelines, which includes computer vision and AI methodologies, for spatial and single cell transcriptomic and image datasets. She is the Director of Panoramics – A Vision, a pan-Canadian spatial and single cell working cluster bringing spatial and single cell scientists together for scientific debate, education and discussion.

Professor Abou Elela obtained his Ph.D. from University of Guelph in 1994 where he generated a system for studying ribosomal RNA processing in vivo and demonstrated the role of rRNA in translation. During his postdoctoral study at the University of California Santa Cruz he revealed the function of the first orthologue of eukaryotic RNase III and demonstrated its role in pre-rRNA processing. Prof. Abou Elela joined the Université de Sherbrooke in 1997 and became a member of the oncology group of the Centre de recherche clinique and the RNA group. Few years later he became the director of Sherbrooke laboratory of functional genomics, the scientific director of Genome Quebec RNomics platform, and the coordinator of the RiboClub. In 2013 Prof. Abou Elela became Canada Research Chair in RNA Biology and Cancer Genomics. Recent work in Abou Elela lab demonstrated that RNA is a major source of cancer biomarkers and may predict tumour behaviour and drug resistance. His research has also indicated that messenger RNA is programmed to respond to cellular signals and degrades rapidly under exposure to drugs and other cellular stresses. Abou Elela aims to develop a model to explain how RNA production and degradation can influence cellular functions.

The Pai Lab at OICR analyzes high-throughput multi-omic data in the healthy developing and adult brain, and in pediatric and adult brain cancer, to identify diagnostic and prognostic biomarkers for eventual clinical implementation. We work with data from genome sequencing technologies at single-cell resolution (e.g., scRNAseq) and bulk tissue (e.g., RNAseq, WGBS, EMseq, ChIPseq), with sample sizes ranging to cohort-scale. We specialize in understanding the role of the non-coding genome in disease progression.

Dr. Sorana Morrissy completed her PhD in Medical Genetics at the University of British Columbia, Vancouver, BC, under the supervision of Dr. Marco Marra.  She pursued post-doctoral research in translational genomics in Dr. Michael Taylor’s lab at the Hospital of Sick Children in Toronto, ON.  Throughout her training she gained extensive experience with cutting-edge high-throughput sequencing technologies and computational analyses in the field of cancer research, with a particular focus on understanding tumor heterogeneity and recurrent disease.

Dr. Steven Hallam is a molecular biologist, microbial ecologist, entrepreneur, and innovator with over two decades of experience conducting field and laboratory research at disciplinary interfaces. He is a former Canada Research Chair in Environmental Genomics and current Professor in the Department of Microbiology and Immunology and program faculty member in the Bioinformatics and Genome Sciences and Technology training programs at the University of British Columbia. Dr. Hallam is the founding director of the ECOSCOPE innovation ecosystem, founding co-director of the Biofactorial automation core facility in the Life Sciences Institute and co-director of the Bradshaw Research Institute for Minerals and Mining (BRIMM) Microbiome Theme. His research intersects microbial ecology, biological engineering, and bioinformatics with specific emphasis on the creation of functional screens and computational tools that reveal hidden metabolic powers of microorganisms at the individual, population, and community levels of biological organization.