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B.Ed. Chemisty/Mathematics (University of Toledo)
PhD Physical Chemistry/Mathematics (Wayne State University)
NIH Post-Doctoral Fellow Laser Chemistry (Cornell University)
Agent Based Modeling of Emergency Response
Natural and human-caused disasters leave both long-term geospatial and human scars. Recent catastrophic events such as the 2008 Sichuan earthquake that killed at least 68,000 people, the 2010 Haiti earthquake that killed over 200,000 people, or the 9–11 terrorist attacks that killed not only building occupants but also emergency response personnel, have left their historical mark. Although geospatial images of each of these events prior to and immediately after the event can provide physical details, ultimate scenario outcome following the disaster is of course absent and unknown. It is the goal of this project to investigate the use of agent-based modeling combined with geospatial information to dramatically improve the effectiveness and safety of emergency response personnel.
This project aims at developing methods for rapidly analyzing video and sequential images of crowds of people to determine when a peaceful crowd may be becoming panicked and potentially dangerous. The ultimate goal is a system that could quickly analyze the movement of a crowd to predict whether it is about to become chaotic.
If the system proves successful, it should be useful in monitoring events in real-time for the purpose of disaster response, law enforcement, and peacekeeping, as well as for analyzing and simulating crowd movement offline for the purpose of better disaster preparedness and urban planning.
Hydrostatic Modeling of Deadly Gas Emissions from African Lakes
In 1986 Lake Nyos in the Northwest Province of Cameroon released a large cloud of carbon dioxide into the atmosphere killing 1,700 people and 3,500 livestock in nearby villages. In addition there have been several smaller disasters from similar lakes in Africa. These lakes are some of the deepest in the world.
Lake Kivu ranks fifteenth with a maximum depth of 480 meters. In the rift valley bordered by the Democratic Republic of Congo and Rwanda, it is one of the African Great Lakes with a maximum length of 89 km and a maximum width of 48 km. With an estimated dissolved carbon dioxide volume of 256 cubic kilometers and 65 cubic kilometers of methane, it too has the potential of exploding and killing most of the neighboring 2 million inhabitants. It is at these depths, under extreme pressure that the gasses lie dissolved and dormant. However, with neighboring active volcanoes and the potential of landslides caused be runoff and extensive deforestation, a potential disaster could happen at any time with little or no warning.
Our unique effort in hydrostatic modeling is directed towards identifying the magnitude of the natural perturbation that could trigger the catastrophic release of a deadly volume of gas. Once quantification of the energy required to cause such a release of gas is known, then the commitment event, e.g. earthquake, volcanic eruption, landslide, can be identified followed by disaster monitoring and prediction.
Agent-Based Modeling of Organizational Silos and Impact on Innovation
Academic and many government institutions are generally organized into departments of highly specialized, like-disciplined individuals. However, industries are often organized along functional lines. One might then ask:
- Why is this true and what are the strengths and weaknesses of each organizational structure?
- Is this structure self-organized or does it result because of administrative dictates and convenience?
- Is this organizational structure the best to foster innovation, exploit discoveries, further knowledge, and improve general social welfare?
Although Agent-Based Modeling has been used to study the diffusion of innovation, we believe we have a unique method to model not only the creation of knowledge, but also its diffusion and growth.