SEMINAR: Integrating Human Performance in the Design Process

Abstract:

The role of technology in safety-critical systems is to improve human and system performance. However, many systems do not comprehensively consider human needs (cognitive, physical, social) and human variability. The absence of human considerations in the design process can lead to avoidable use errors during technology interaction. Design decisions are often made without empirical evidence of its impact on human performance. To establish a safe and effective interaction between the human user and safety-critical systems, human factors principles must be addressed early and iteratively throughout the design process. The seminar will discuss approaches to: 1) behaviorally model the human user, 2) empirically evaluate human response through simulated use testing, and 3) perform descriptive and predictive modeling of human response. Integration of insights from empirical data analyses into system design decisions and design risk mitigation will be addressed for several applications domains, including healthcare, defense, and energy.

Biography:

Dr. Monifa Vaughn-Cooke is an Assistant Professor of Mechanical Engineering and a Core Faculty member of the Reliability Engineering Graduate Program at the University of Maryland, College Park. Her expertise is in the area of human reliability and device design, with a focus on improving human performance for hybrid systems (human-software-hardware). Dr. Vaughn-Cooke’s research is primarily focused on empirical design validation through human experimental testing and has been funded across a variety of safety-critical domains (healthcare, energy, defense). She has worked with numerous federal agencies to integrate human-centered design practices into regulatory approval processes. Dr. Vaughn-Cooke is the Director of the UMD Hybrid-System Integration and Simulation Laboratory which is a state-of-the-art computational and experimental facility equipped with 2D and 3D simulation tools, a suite of neurophysiological sensors, and usability testing equipment, to perform and analyze data from human performance experiments.