Stochastic Modeling in Biological, Physical and Social Sciences: Theory and Applications
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Organizer(s): |
Name:
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Affiliation:
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Country:
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Wai-Tong (Louis) Fan
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Indiana University Bloomington
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USA
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Krutika Tawri
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University of California, Berkeley
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USA
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Chuntian Wang
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The University of Alabama
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USA
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Roger Temam
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Indiana University Bloomington
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USA
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Abstract:
| | Stochastic models play a significant role in mathematics, science and engineering. With ever-increasing applications in biology, climate science, physics, engineering and social science, these models offer insight into the dynamics, phase transitions and other phenomena of the complex system under study. Furthermore, lying at the intersection of probability, statistics, partial differential equations and many areas in mathematics, they provide a plethora of new and interesting mathematical challenges.
Motivated by the need from within and beyond the mathematical community, our session will focus on recent advances of stochastic modeling in various application fields. We aim to bring together a diverse body of researchers to stimulate discussions about such models from both theoretical and applied points of view. Our topics include the regularity, properties and applications of stochastic partial differential equations, stochastic and statistical dynamics, stochastic numerical analysis, implementations, and simulations. |
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List of approved abstract |
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