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What if ?
explaining the past - predicting the future
mathematical & computational
models & simulations


Anita Layton WebSite
MATH 161FS: Introduction to Mathematical Modeling in Biology (R, QS)

Lead Faculty

Anita Layton, Associate Professor, Mathematics
Nick Gessler, Research Associate, ISIS

Affliated Faculty:

Emily Braley, Assistant Professor of the Practice, Mathematics
James Clark, Professor, Nicholas School, Biology, Statistical Science
Katherine Hayles, Professor, Literature
Mark Kruse, Associate Professor, Physics
Bill Seaman, Duke Institute for Brain Sciences
Xiaobai Sun, Professor, Computer Science


Nick Gessler WebSite
ISIS 170FS: Artificial Life, Artificial Culture & Evolutionary Computation (SS, QS, STS)

Emily Braley WebSite
MATH 182FS: Mathematics of Finance (QS)

Overview

Mathematical and computational models can be used to develop data to help us understand the complex systems around us. The development of those data can be done analytically, statistically, or by means of simulations over time. In the social sciences, simple simulations are used to implement models of segregation, assimilation and the diffusion of cultural traits. More complex models test theories of economics by creating a population of agents who exchange commodities at prices they determine from local information. Still more complex simulations determine the outcome of social policies under different conditions. These models and simulations are used in domestic, international, diplomatic and military operations the world over to explore the envelope of possibilities resulting from different known and unknown factors through the creation of counterfactual "What if ?" scenarios.


Xiaobai Sun WebSite
COMPSCI 190FS: Introduction to Graphical Models with Applications to Making Brain Maps (QS)

http://isis.duke.edu/gessler/whatif