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MGSA Grad Student Seminar - Xige Yang

Xige Yang
September 4, 2018
5:15PM - 6:15PM
Cockins Hall 240

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Add to Calendar 2018-09-04 17:15:00 2018-09-04 18:15:00 MGSA Grad Student Seminar - Xige Yang Title: Bridging Mathematics and Life Science: Snapshots From Reaction-Diffusion Equations Speaker: Xige Yang (Ohio State University) Abstract: Since Alan Turing's pioneering work in 1952, reaction-diffusion equations (RDEs) have been rapidly attracting scientists and researchers with different background. In my talk, I will give a friendly introduction to RDEs from various points of view. First, I will start with some simple simulations of an RDE, then introduce basic theoretical results of RDEs. Second, due to limitations of theoretical results, numerical methods will be addressed. In particular, a new field called numerical algebraic geometry (i.e. how to solve polynomial systems using a computer) will be introduced in order to find multiple solutions of an RDE, which may well also bring some new insights into applications of classical algebraic geometry. Finally, if time allows, I will briefly show how data science can help to avoid the mathematical difficulties of RDEs by providing an equation-free solution to them. Cockins Hall 240 Department of Mathematics math@osu.edu America/New_York public

Title: Bridging Mathematics and Life Science: Snapshots From Reaction-Diffusion Equations

SpeakerXige Yang (Ohio State University)

Abstract: Since Alan Turing's pioneering work in 1952, reaction-diffusion equations (RDEs) have been rapidly attracting scientists and researchers with different background. In my talk, I will give a friendly introduction to RDEs from various points of view. First, I will start with some simple simulations of an RDE, then introduce basic theoretical results of RDEs. Second, due to limitations of theoretical results, numerical methods will be addressed. In particular, a new field called numerical algebraic geometry (i.e. how to solve polynomial systems using a computer) will be introduced in order to find multiple solutions of an RDE, which may well also bring some new insights into applications of classical algebraic geometry. Finally, if time allows, I will briefly show how data science can help to avoid the mathematical difficulties of RDEs by providing an equation-free solution to them.

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