Dr. Lubna Daraz is an Assistant Professor in the School of Library and Information Science, Faculty of Arts and Sciences at the University of Montreal. Before joining the University of Montreal, Dr. Daraz served as an Assistant Professor of Medicine and Research Fellow at Mayo Clinic, Rochester, Minnesota. United States.

Dr. Daraz holds a Ph.D. in Health Sciences From McMaster University and a Master’s in Library and Information Sciences from the University of Toronto.

Dr. Daraz brings expertise in Evidence-based Practice, Knowledge Translation, Digital Health Information-Seeking, Health Literacy, Health Informatics, Implementation Science, and Disadvantaged Populations.

Academic Positions

  • Present2020

    Assistant Professor, Information in the Health Sector.

    School of Library and Information Science. Faculty of Arts and Sciences. University of Montreal.

  • 20202018

    Assistant Professor of Medicine

    College of Medicine and Science. Mayo Clinic, Rochester, Minnesota. USA

  • 20202016

    Research Fellow.

    Evidence-based Practice Research Program. Mayo Clinic, Rochester, Minnesota. USA

Education & Training

  • Ph.D. 2011

    Ph.D. in Health Sciences

    McMaster University

  • M.I.S.t. 2006

    Master's in Information Studies

    University of Toronto


Digital health information-seeking
Evidence-based Practice
Health Literacy

Health Informatics

Knowledge Translation
Implementation Science
Qualitative and Mixed-method
Reliability of Online health information
Social determinants of health
Data Science
Disadvantaged and vulnerable populations

Research Expertise

Knowledge is empowerment. Reliable health knowledge (information) has a tremendous impact on the social and economic well-being of Canadians.

My research involves collaboration between interdisciplinary teams to study the digital health information-seeking behaviour of people and develop evidenced-based tools and frameworks that may improve health outcomes and quality of life for the vulnerable, underserved, and disadvantaged populations.