Bill Burns completed his Ph.D. at the University of Oregon in Decision Science and subsequently held positions as a professor at the University of Iowa and UC Davis before moving to San Diego. He is currently a research scientist at Decision Research (Eugene, OR), an institute that focuses on judgment, decision making and risk perception, and is also associated with the National Center for Risk and Economic Analysis of Terrorism Events at the University of Southern California and the Center for Accelerating Operational Efficiency at Arizona State University. He teaches probability, statistical regression and forecasting part-time at California State University San Marcos, and advises on student-consulting projects. His work has been funded by the U.S. Department of Homeland Security and the National Science Foundation. Research and interviews related to the public’s response to the different crises have appeared in academic journals such as Management Science, Risk Analysis, Decision Analysis and Journal of Applied Communication Research and media such as The Wall Street Journal, The Huffington Post and National Public Radio. He has been the guest editor for a special issue in Risk Analysis entitled “Risk Perception and Behaviors: Anticipating and Responding to Crises.” He has also given keynote addresses at the Oregon Health Science University/Portland State University Symposium (2018), International Crisis and Risk Communication Conference (2017), and IEEE Intelligence Security Informatics Annual Conference (2013).
Dr. Burns spent three summers working in Washington D.C. at the TSA on a Department of Homeland Security University Faculty Fellowship. He has also helped organize the annual CREATE/TSA Symposium (now ASU/TSA Symposium) since its beginning in 2015. Work with the TSA has focused on modeling adaptive threats to commercial aviation. More generally, investigations over the near future focus on: understanding the social psychology behind enhancing public resilience to crisis, demotivating terrorists and understanding and mitigating factors that contribute to public susceptibility to misinformation in media stories (e.g., “fake news” stories in traditional and social media).