Gairdner Alberta Partnered AI + Health Research Symposium

Dr. Natalie Pageler is a board-certified pediatric intensivist and clinical informaticist. She is Associate Dean of Maternal Child Health and the inaugural Division Chief of Clinical Informatics in the Department of Pediatrics, co-founder and former Program Director of the Stanford Clinical Informatics Fellowship, and Clinical Professor at Stanford University School of Medicine. She also served as Chief Health Informatics Officer at Stanford Children's for the last decade. She spearheaded the development of the Stanford Children’s Digital Health and Translational Data Science Programs, led cutting-edge local and national efforts to facilitate health information sharing and digital engagement, and implemented computerized decision support tools to help achieve the best health outcomes for children and families.

Dr. Amber Simpson is a Professor in the Department of Radiology & Diagnostic Imaging at the University of Alberta. She is also a Fellow of the Alberta Machine Intelligence Institute (Amii), a CIFAR AI Chair, and the Inaugural Director of the Dianne & Irving Kipnes Health Research Institute. Dr. Simpson is a computer scientist by training and an expert in cancer imaging artificial intelligence and develop innovative computational strategies, and translate complex biological data into real-world health solutions to improve human health, ensuring research infrastructure is patient-centred and scalable.

Dr. Amol Verma is a physician and scientist in General Internal Medicine at St. Michael’s Hospital and the Temerty Professor of AI Research and Education in Medicine at the University of Toronto. He is a health services researcher, studying and improving hospital care using electronic clinical data. Dr. Verma co-founded and co-leads GEMINI, Canada’s largest hospital clinical data research network, which is collecting data from >30 hospitals in Ontario.

Dr. Hosna Jabbari is the University of Alberta Engineering Research Chair in Computational Biology and Professor of computational biology/bioinformatics in the Department of Biomedical Engineering and the Department of Electrical and Computer Engineering (Cross Appointed). She also serves as the Director of the Computational Biology Research and Analytics Laboratory (COBRA Lab). Her research focuses on uncovering the underlying mechanisms of human diseases through a transcriptomic perspective. Dr. Jabbari has a comprehensive background in predicting the complex structure of RNA and applying this knowledge to therapeutic developments.

Dr. Jonathan Stokes is an Assistant Professor in the Department of Biochemistry and Biomedical Sciences at McMaster University. He leads an interdisciplinary research group developing and applying machine learning methods to drug discovery, with an emphasis on antibiotics. Dr. Stokes is also co-founder and Chief Scientific Officer of Stoked Bio.

Dr. Nevan Krogan is a molecular and systems biologist. He is a professor and the director of the Quantitative Biosciences Institute at the University of California San Francisco School of Pharmacy. He is also a senior investigator at the Gladstone Institutes. Dr. Krogan's lab at UCSF focuses on developing and applying quantitative, systematic proteomic and genetic approaches to study complex biological and biomedical problems. At present time, the Krogan group is focused on studying cancer, infectious disease and psychiatric disorders.

Dr. Thomas Kaiser is physician-scientist dedicated to designing next generation medicines for rare diseases. Trained in artificial intelligence, organic chemistry and clinical medicine, he brings a unique perspective on machine learning for drug design and development as well as general techniques in artificial intelligence for the natural and clinical sciences. He is co-founder and CSO of Avicenna Biosciences, a company developing disease-modifying clinical candidates for ALS and Parkinson's disease. He is also an operating partner of DCVC Bio, a leading venture capital firm in San Francisco.

Dr. Vallijah Subasri is an AI Scientist at Peter Munk Cardiac Centre where she leverages artificial intelligence to develop strategies and tools for precision medicine in cardiovascular diseases. Dr. Subasri's previous work focused on using genomics and machine learning to understand the clinical heterogeneity of pediatric cancers, develop risk prediction models for personalized patient management and ensuring the responsible deployment of clinical machine learning models, with a focus on distribution shifts and fairness.