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Westlake Math Colloquium第七十二期 | Fanghua Lin: New Approaches to the Gradient Flow of Map
时间
2025年4月18日(周五)
14:00-15:00
地点
E10-211
主持
Thierry De Pauw, ITS
受众
全体师生
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名家讲座
Westlake Math Colloquium第七十二期 | Fanghua Lin: New Approaches to the Gradient Flow of Map
时间:2025年4月18日(周五)14:00-15:00
地点:E10-211
主持人:Thierry De Pauw, ITS
主讲人:Fanghua Lin, New York University
主讲人简介:Fanghua Lin is a Silver Professor of Mathematics at the Courant Institute of Mathematics, New York University. He graduated from Zhejiang University in 1981 and received his Ph.D. from the University of Minnesota in 1985. From 1985 to 1988, he worked as a postdoctoral fellow at the Courant Institute, MSRI Berkeley, and IAS Princeton. In 1988, he became a professor at the University of Chicago and has been a professor at New York University since 1989. In 1990, he gave a 45-minute lecture at the International Congress of Mathematicians. In 2002, he won the Bôcher Prize of the American Mathematical Society. In 2004, he became a member of the American Academy of Arts and Sciences. In 2015 and 2018, he was named a Fellow of the American Mathematical Society and a Fellow of SIAM. Professor Fanghua Lin has made extensive and outstanding contributions in mathematical fields such as partial differential equations, geometric measure theory, and geometric analysis. In particular, he has made a series of outstanding works on the mathematical theory of liquid crystals, harmonic mappings, homogenization theory, quantized uniqueness theory, and Ginzburg-Landau Equations. Professor Lin has published many monographs and more than 200 papers in internationally renowned journals such as Acta Math. Ann. Math., JAMS, Invent. Math., and CPAM.
讲座主题:New Approaches to the Gradient Flow of Map
讲座摘要: I shall briefly discuss two new approaches to gradient flow of harmonic maps both due to De Giorgi around the mid-1990s. Recently we can use one of them to settle a couple open questions. The other one seems to be more natural, and an earlier version was well-known. However, one meets more analytical challenges that only in low dimensions one can show it indeed leads to good weak solutions.