南京大学计算机科学与技术系

软件新技术与产业化协同创新中心

摘 要：

Geometric data is ubiquitous nowadays, and is becoming more and more complex. Effectively analyzing and processing such data is an important and challenging task. This leads to the need of developing efficient algorithms and data structures for solving computational problems on geometric datasets, which is the main subject of the field Computational Geometry. My research mainly focuses on designing geometric algorithms and data structures that can be theoretically proved to have good performances. These algorithms and data structures are usually more reliable, more robust, and hence more preferable than the ones without theoretical guarantees. In this talk, I will give an overview of some important problems in Computational Geometry as well as several state-of-the-art algorithms and data structures for these problems developed by me and other coauthors.

报告人简介:

Jie Xue is currently a postdoctoral scholar at the University of California, Santa Barbara. He received his Ph.D. degree in Computer Science with a minor in Math from the University of Minnesota, Twin Cities, in 2019. His main research area is Computational Geometry, with a particular focus on designing (theoretical) algorithms and data structures for solving geometric problems. His work has been published in various top venues in Computational Geometry and Algorithms, such as SoCG, SODA, DCG, JoCG, etc.

时间:12月13日（星期日）10:00-11:00

ZOOM link          密码：2020

https://us02web.zoom.us/j/5221214665