Catherine Burns

Professor, Systems Design Engineering

Director, Centre for Bioengineering and Biotechnology

University of Waterloo




Catherine M. Burns is Professor in Systems Design Engineering at the University of Waterloo, Canada where she directs the Advanced Interface Design Lab and the Centre for Bioengineering and Biotechnology (CBB). Catherine’s research is in human factors engineering where she is well known for her work in Cognitive Work Analysis, Ecological Interface Design and the development of decision support systems.  In this area she has contributed over 250 publications and is the co-author of seven books.  She is a Fellow of the Human Factors and Ergonomics Society.  She has served as Program Chair for the Cognitive Engineering and Decision Making Technical Group of the Human Factors and Ergonomics Society, Chair of Canada’s Natural Science and Engineering Research Council grant committee for Industrial and Systems Engineering and currently sits on the editorial boards of five journals.  Catherine has a track record of conducting industry relevant research and building strong industrial partnerships and regularly serves as a consultant for companies in a range of industries.  Catherine’s recent research projects have been exploring how naval crews work with data fusion systems, decision making support for automated financial trading, interactions with automated vehicles, and support for improved medication management.

Keynote: Understanding, supporting, and redesigning cognitive work


We understand the value of measuring workload for job design and the benefits that can come from understanding the nature of that workload.  Cognitive work analysis (CWA) is a framework that has been used in many settings to describe various aspects of work.  In this talk I will present an introduction to Cognitive Work Analysis and some of the foundational research that has used the approach.  I will also discuss how work can be supported using the insights obtained from a CWA.  The key questions facing us though is the prediction of work, and how new technologies will change workload.  I will look at how CWA can be used to anticipate different kinds of cognitive work, depending on the technology that is being considered.  Further, I will also discuss our emerging ideas on how certain work patterns could be designed from the analysis of work and triggered reliably.  Although the basis of this discussion will be CWA, the ideas are applicable to other work modelling approaches.  Given the current pace of technology development and innovation, methods that can anticipate the workload for users, ahead of empirical studies, are becoming very important for appropriate technology selection.