People
The UBC AI and Health Network brings together UBC investigators from interdisciplinary fields that span data science, health system research and biomedicine. By bridging the latest advances in AI with world-leading expertise in clinical, population health and biomedical sciences, the Network is advancing patient-centered AI solutions in Canadian health care.
Co-Leaders
Raymond Ng, PhD
Professor, Department of Computer Science
Canada Research Chair in Data Science & Analytics
Dr. Ng is a data scientist with a passion for using AI to streamline complex challenges in the healthcare system and improve patient outcomes. His research areas are data mining, text mining, health informatics, sensor analytics and databases. In his work on genomics with the PROOF Centre of Excellence for the Prevention of Organ Failures, he focuses on the development of biomarker panels for various conditions related to organ failures in hearts, lungs or kidneys. Dr. Ng has received numerous prestigious awards, including the Life Sciences BC Scientific Excellence Award in 2024 and Fellow of the Royal Society of Canada in 2021.
Email: [email protected]
Anita Palepu, MD, MPH, FRCPC, MACP, FCAHS
Professor & Head, Department of Medicine
Dr. Palepu is committed to co-creating a strong health data science ecosystem to improve the care she and her clinical colleagues provide throughout the province. She is a renowned general internist internationally recognized for her research with marginalized populations. Actively involved in undergraduate and postgraduate education, she has received numerous awards for teaching excellence and health advocacy. She leads UBC’s Research Excellence Cluster in Data Science and Health, contributing to health data science and AI education that is now critical for healthcare professionals.
Email: [email protected]
Faculty Members
Ali Bashashati, PhD
Associate Professor, Department of Pathology & Laboratory Medicine and School of Biomedical Engineering
Dr. Bashashati is interested in developing machine learning algorithms to combine various sources imaging, digital pathology and ‘omics data in the context of cancer. Using machine learning, he aims to improve pathology diagnostic efficiency, identify new biomarkers for treatment selection and derive biological insights for various health conditions with major emphasis on cancer.
Email: [email protected]
Jörg Gsponer, MD, PhD
Professor & Head, Department of Biochemistry & Molecular Biology
Developing and using advanced computational methods, Dr. Gsponer’s research aims to better understand protein-mediated cellular processes in physiological and disease contexts. He has made significant contributions to our understanding of the working mechanisms of intrinsically disordered proteins, and he was awarded a Faculty of Medicine Distinguished Achievement Award for Overall Excellence in recognition of his work.
Email: [email protected]
Stephen Lam, MD, FRCPC
Professor, Department of Medicine
Leon Judah Blackmore Chair in Lung Cancer Research, BC Cancer Research Centre
Dr. Lam’s research focuses on early detection and chemoprevention of lung cancer. His long-term goal is to translate scientific research in lung cancer screening for implementation at the population level to improve lung cancer outcomes. As part of the Pan-Canadian Early Detection of Lung Cancer Study Network, Dr. Lam and colleagues have developed and prospectively validated a web-based lung cancer risk prediction tool to identify smokers at sufficient risk for screening with low-dose CT and to evaluate the incremental value of blood and exhaled breath biomarkers. He is also part of a team to use radiomics and deep learning tools to address the important issue of screening interval and duration.
Email: [email protected]
Dean Regier, PhD
Director, Academy of Translational Medicine
Associate Professor, School of Population & Public Health
Dr. Regier’s research focuses on translational medicine, regulatory science, and the economics of precision medicine, generating patient-oriented and AI-supported real-world evidence for sustainable learning healthcare systems. The Academy of Translational Medicine (ATM) connects people from science, business, health, and government to accelerate the translation of scientific discoveries into clinical practice. Dr. Regier has previously served on BC’s Drug Benefit Council, which makes evidence-informed recommendations to the Ministry of Health about the listing of drugs on the PharmaCare program formulary. He currently collaborates with Health Canada, Canada’s Drug Agency (CDA-AMC), and Quebec’s Institut national d’excellence en santé et en services sociaux (INESSS) to streamline regulatory and reimbursement pathways from discovery to patient health.
Email: [email protected]
Sriram Subramaniam, PhD
Professor, Biochemistry & Molecular Biology
Gobind Khorana Canada Excellence Research Chair in Precision Cancer Drug Design
Dr. Subramaniam uses powerful cryo-electron (cryo-EM) microscopes to accelerate drug development for cancer, neurological and infectious diseases, and more. At UBC and his UBC spin-off company, Gandeeva Therapeutics, his team is working to accelerate the development of new precision medicines by integrating cryo-EM with AI. Dr. Subramaniam is also an investigator with Canada’s Immuno-Engineering and Biomanufacturing Hub, where he is leading a project to develop a suite of ready-to-deploy antibody treatments for current and emerging health threats using structural biology approaches and AI-powered biologics discovery.
Email: [email protected]
Daniel Vigo, MD, Psych, DrPH
Associate Professor, Department of Psychiatry and School of Population and Public Health
BC’s Chief Scientific Advisor for Psychiatry, Toxic Drugs and Concurrent Disorders
Dr. Vigo’s research focuses on needs-based planning for mental health and substance use disorders, student e-mental health and psychiatric epidemiology studies of regional, national and global scope. The goal of his e-mental health portfolio is to create, administer and evaluate online e-interventions and screening tools, as well as to integrate them with existing brick and mortar services. He is also working in collaboration with data scientists to develop algorithms to predict the risk of developing mental and substance use disorders. By using machine learning techniques and applying those to health service utilization data, his goal is to facilitate access to effective treatments.
Email: [email protected]