报告人：韩晓莹
报告地点：腾讯会议ID:307 600 284;会议密码:221216
报告时间：2022年12月16日星期五10:30-11:30
邀请人：李勇、冀书关
报告摘要：
A selection of lattice models arising from biological and artificial neural networks, in particular, recurrent neural networks, will be introduced. The emphasis is on modelling of interconnection structures among neurons, and how they affect the stability of neural networks. Long term dynamics in terms of existence and properties of attractors will be discussed, using theory and techniques of dynamical systems.
主讲人简介：
Dr. Xiaoying Han graduated from the Special Class for the Gifted Young at the University of Science and Technology of China, with a B.E. in Computer Science in 2001. She received her Ph.D. in Mathematics from the State University of New York at Buffalo in 2007 and has since worked at Auburn University. She was promoted to full professor in 2017, awarded the Marguertie Scharnagle Endowed Professorship in 2018, and obtained College of Sciences and Mathematics Young Faculty Scholar Award in 2021. In 2020 she was named a U.S. Fulbright Scholar, funding her for a research visit to Brazil. She is the co-editor-in-chief for the journal Discrete Contin. Dyn. Syst. Ser. S, as well as an associate editor for a few other journals including Discrete Contin. Dyn. Syst. Ser. B, Stoch. Anal. Appl., etc. She has co-authored 4 monographs, and published around 70 papers in journals including SIAM J. Appl. Math., J. Differential Equations, SIAM J. Math. Anal., etc.
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