Zhuang*, Jun (University at Buffalo)

Jun Zhuang Speaker Photo 2021 Small 50

Dr. Jun Zhuang
University at Buffalo
Buffalo, New York

Website: http://www.eng.buffalo.edu/~jzhuang/

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Game Theory and Disaster Management

Society is faced with a growing amount of property damage and casualties from man-made and natural disasters. Developing societal resilience to those disasters is critical but challenging. In particular, societal resilience is jointly determined by federal and local governments, private and non-profit sectors, and private citizens. We will present a sequence of games among players such as federal, local, and foreign governments, private citizens, and adaptive adversaries. In particular, the governments and private citizens seek to protect lives, property, and critical infrastructure from both adaptive terrorists and non-adaptive natural disasters. The federal government can provide grants to local governments and foreign aid to foreign governments to protect against both natural and man-made disasters; and all levels of government can provide pre-disaster preparation and post-disaster relief to private citizens. Private citizens can also, of course, make their own investments. Th  e tradeoffs between protecting against man-made and natural disasters, specifically between preparedness and relief, efficiency and equity, and between private and public investment, will be discussed. Recent research on big data analytics and decision modeling on social media rumor spreading and management will also be discussed.

Appropriate audience: Undergraduate students

Crisis Communication and Rumor Management Using Social Media During Disasters

Social media has been more and more used by government and nongovernment organizations, and private citizens for crisis communication during disasters. However, few research has studied the users’ behavior when facing rumors and debunking information. In this research, we first study the effectiveness of crisis communication and how retweet and mention could help improve crisis information impression. Millions of tweets posted during Hurricane Sandy in 2012 are collected and analyzed. Second, we investigate four cases of rumor responding and debunking behaviors of Twitter users during Hurricane Sandy in 2012 and Boston Marathon bombings in 2013. We find that for users who were misinformed and reacted by posting tweet(s), they could respond to this rumor by: spreading (~86%), seeking confirmation (~9%), or doubting (~10%). Given rumor spreading users were debunked, they would respond by: deleting rumor tweets (~10%), clarifying rumor information with a new tweet (~19%), or doing nothing (~78%). Finally, we discuss the optimal debunking strategies dealing with potential rumor information, and the corresponding consequences on the downstream information sharing. We also use simulation to study the impact of different network information flow structure. This research provides some novel insights on crisis communication and rumor management using social media during disasters.

Appropriate audience: Undergraduate students

Cost-benefit Analysis of Fire Protection Resource Allocation in the United States: Models and a 1980-2014 Case Study

Fire-related hazards and incidents are an everyday phenomenon, and firefighting in the United States owe to more than one million firefighters in about 30,000 fire departments across the country. The estimated total cost of fire was $329 billion in 2011. Leveraging the National Fire Incident Response System (NFIRS) data set, we conduct a data-driven study to propose empirical and theoretical models to assess risk levels and quantitatively measure effectiveness of investments. We then study the optimal risk-reduction strategies, and optimal resource allocation strategies given a total budget constraint. We will also discuss public-private partnership, equity, and optimal routing in fire protection. This study would benefit policymakers and analysts in fire protection and safety, to save lives and other losses.

Appropriate audience: Undergraduate students

Balancing Congestion and Security in the Presence of Strategic Applicants with Private Information

Concerns on security and congestion appear in security screening which is used to identify and deter potential threats (e.g., attackers, terrorists, smugglers, spies) among normal applicants wishing to enter an organization, location, or facility. Generally, in-depth screening reduces the risk of being attacked, but creates delays that may deter normal applicants and thus, decrease the welfare of the approver (authority, manager, screener). In this research, we develop a model to determine the optimal screening policy to maximize the reward from admitting normal applicants net of the penalty from admitting bad applicants. We use an M/M/n queueing system to capture the impact of security screening policies on system congestion and use game theory to model strategic behavior, in which potential applicants with private information can decide whether to apply based on the observed approver's screening policy and the submission behavior of other potential applicants. We provide analyt  ical solutions for the optimal non-discriminatory screening policy and numerical illustrations for both the discriminatory and non-discriminatory policies. In addition, we discuss more complex scenarios including robust screening, imperfect screening, abandonment behavior, and complex server networks.

Appropriate audience: Undergraduate students

Education & Background

  • PhD, University of Wisconsin-Madison

Dr. Jun Zhuang is Morton C. Frank Professor, Director of Graduate Studies, and Director of the Decision, Risk & Data Laboratory, Department of Industrial and Systems Engineering, School of Engineering and Applied Sciences (SEAS) at the University at Buffalo (UB), the State University of New York (SUNY). Dr. Zhuang has a Ph.D. in Industrial Engineering in 2008 from the University of Wisconsin-Madison. Dr. Zhuang's long-term research goal is to integrate operations research, big data analytics, game theory, and decision analysis to improve mitigation, preparedness, response, and recovery for natural and man-made disasters. Other areas of interest include applications to health care, sports, transportation, supply chain management, sustainability, and architecture. Dr. Zhuang has been a principal investigator of over 30 research grants funded by the U.S. National Science Foundation (NSF), by the U.S. Department of Homeland Security (DHS), by the U.S. Department of Energy, by the U.S. Air Force Office of Scientific Research (AFOSR), and by the National Fire Protection Association (NFPA).

Languages Spoken:

English, Mandarin