Aminah Robinson Fayek, PhD, PEng

Photo of Chairholder Aminah Robinson Fayek

NSERC Industrial Research Chair in Strategic Construction Modeling and Delivery
Professor, Construction Engineering and Management
Ledcor Professor in Construction Engineering

Dr. Aminah Robinson Fayek is a tenured professor with the Department of Civil and Environmental Engineering at the University of Alberta. Since joining the Department in 1997, Dr. Robinson Fayek has become a respected member of Alberta’s construction industry and an internationally recognized expert in fuzzy logic and fuzzy hybrid modeling techniques for intelligent decision support in the construction industry. She holds the prestigious Ledcor Professorship in Construction Engineering, with a mandate to advance research, scholarship, and learning in construction.

In 2007, Dr. Robinson Fayek became the NSERC Associate Industrial Research Chair in Construction Engineering Management at the University of Alberta. As the Associate Chair, she developed a successful formula for collaborative research between the University and industry. Her research partnerships produced studies in subjective knowledge elicitation and consensus reaching, contractor prequalification, industry performance benchmarking, reducing field rework, reducing workforce absenteeism, and improving supervisory training. The research also led to the development of several valuable applications for industry, including a contractor prequalification tool, a foreman skills development tool, and a workforce absenteeism tracking tool.

In January 2012, Dr. Robinson Fayek became the NSERC Senior Industrial Research Chair (IRC) in Strategic Construction Modeling and Delivery. The IRC specializes in developing hybrid intelligent decision support systems that incorporate fuzzy logic with other modeling techniques, such as artificial neural networks, genetic algorithms, and simulation. The research has significant potential to change the way in which the construction industry models operations and decisions, leading to more accurate and realistic representations of the expert reasoning process and the uncertainty involved.