Raymond Ng

Raymond T. Ng is a Professor of Computer Science at the University of British Columbia (UBC), where he also serves as the Director of the Data Science Institute. He holds a part-time role as the Chief Informatics Officer at the PROOF Centre of Excellence for the Prevention of Organ Failures. Ng's research spans data mining, health informatics, and bioinformatics, with a focus on biomarker discovery for organ failures and computational methods for analyzing medical data. He earned his PhD in Computer Science from the University of Maryland, College Park, and has been a faculty member at UBC since 1992.

Education:

• BSc (Hons.) in Computer Science, University of British Columbia (1986)
• M.Math in Computer Science, University of Waterloo (1988)
• PhD in Computer Science, University of Maryland, College Park (1992)

Research Interests: Ng's work integrates data science with healthcare, including genomic data analysis, biomarker development for COPD and heart failure, and natural language processing for medical text. His projects address challenges in precision medicine, such as non-invasive diagnostics for organ rejection in heart transplants and predicting pulmonary exacerbations in cystic fibrosis. He leads initiatives like the MERIDIAN project to advance ocean acoustic data infrastructure.

Awards:

• Genome BC Award
• Killam Research Prize
• Fellow of the Royal Society of Canada
• Bio-IT Best Practices Award
• CASCON Best Exhibit Award

Grants & Advising: Ng has secured significant funding for projects like PROOF Centre biomarker research and the MERIDIAN data infrastructure. His advisory work focuses on computational biology and data-driven healthcare solutions. He supervises students in machine learning, text mining, and health informatics.

Labs & Teams: Ng oversees the Data Systems and Mining Laboratory and collaborates with interdisciplinary teams at the PROOF Centre and the Natural Language Processing Lab. His work bridges academia and industry, driving translational research in precision health and environmental data science.