Mathematical models intended for computational simulation of complex real-world processes are a crucial ingredient in virtually every field of science, engineering, medicine, and business, and in everyday life as well. Cellular telephones attempt to meet a caller’s needs by optimizing a network model that adapts to local data, and people threatened by hurricanes decide whether to stay or flee depending on the predictions of a continuously updated computational model.
Two related but independent phenomena have led to the near-ubiquity of models: the remarkable growth in computing power and the matching gains in algorithmic speed and accuracy. Together, these factors have vastly increased the applicability and reliability of simulation not only by drastically reducing simulation time, thus permitting solution of larger and larger problems, but also by allowing simulation of previously intractable problems.
The intellectual content of computational modeling comes from a variety of disciplines, including statistics and probability, applied mathematics, operations research, and computer science, and the application areas are also remarkably diverse.
- Air Quality
- Calibration of Computational Models of Cerebral Blood Flows
- Climate and Weather
- Dynamics of Infectious Diseases
- Engineering Methodology
- Granular Materials – Engineering Applications
- Inference and Uncertainty Analysis of Hydrological Models
- Statistical Mechanics of Granular Flow
- Systems Biology
- Terrestrial Models
** To see more in depth information on this program, see the report HERE **