Raj Ratwani, PhD, one of the first researchers and applied engineering experts to conduct real-time error prediction in humans, serves as Vice President, Scientific Affairs, MedStar Health and Director at the MedStar National Center for Human Factors Engineering in Healthcare. In addition, he is an adjunct faculty member at George Mason University in Fairfax, VA. As a researcher, Dr. Ratwani focuses on the cognitive and perceptual processes underlying behavior. He is known for his research in predicting and preventing human error, task interruption and resumption, supervisory control and visual perception. Dr. Ratwani has years of experience in applied human factors engineering and cognitive research in the fields of aviation and defense and is now applying his theories of human cognitive processes to improve healthcare delivery. In addition to his deep understanding of cognitive theories, Dr. Ratwani has a strong background in statistical modeling and is adept in creatively using new technologies to advance his work. He is proficient in quantitative analysis and observational methods, using a wide array of technologies, including eye tracking systems and advanced data visualization tools.
Dr. Ratwani has experience applying human factors engineering to the work environment in both the public and private sectors, including the Defense Advanced Research Projects Agency (DARPA) and the Naval Research Laboratory. He has published more than 25 peer-reviewed publications and is a consulting editor for the Journal of Experimental Psychology: Applied. He also serves as a reviewer for several journals, includingHuman Factors, the International Journal of Human-Computer Studies and the Journal of Cognitive Engineering and Decision Making.
He has received numerous awards for his research, including the Fleishman award for his work in applied experimental psychology, the Alan Berman research publication award and the Cognitive Science Society's Applied Computational Cognitive Modeling prize. He holds memberships in the American Psychological Association, the Cognitive Science Society and the Human Factors and Ergonomics Society.
Dr. Ratwani earned a Ph.D. in human factors/applied cognition (Psychology) from George Mason University in Fairfax, VA, and completed a National Research Council post-doctoral fellowship at the U.S. Naval Research Laboratory.
Dr. Ratwani's research interests include
- Human factors engineering
- Cognition, perception and memory
- Prediction of human error and error avoidance methods
- Effect of interruption, resumption and multi-tasking on worker proficiency and accuracy
- Human-computer interactionsReal-time error prediction
- Data visualization and representation
- Quantitative analysis methods
Predicting and Preventing Skill-Based Errors Using Eye Movements
Dr. Ratwani's work with the U.S. Naval Research Laboratory on understanding the reasons errors occur in the workplace resulted in the development of proven real-time prediction techniques that can predict errors before they occur. Using eye movements as a measure of behavior, he developed mathematical models that are used in a real-time eye gaze system to predict procedural errors. Dr. Ratwani and a colleague have published an article detailing this work in Human-Computer Interaction (2011;26:205-245).
Interruptions, Resumption and Multi-tasking
In this work, Dr. Ratwani studied how people resume tasks following an interruption and methods to reduce the cost of interruptions. He found that by training people how to deal with interruptions, time to task resumption was shortened. This work was conducted for the U.S. Naval Research Laboratory and has been presented at meetings of the Human Factors and Ergonomics Society.
Graphs and Complex Visualizations
In this work, published in the Journal of Experimental Psychology: Applied (2008;14:36-49), Dr. Ratwani and colleagues focused on the cognitive processes people use to obtain information that is presented graphically. This research extended current graph comprehension theories to account for information integration. The authors developed design principles to facilitate the processing of complex graphs and examine specific aspects of graphs, including color, which facilitate human processing. This work was conducted with researchers at the U.S. Naval Research Laboratory and George Mason University.