报告时间：2020年12月5日星期六

腾讯会议ID：676 180 130

第一场：8:30—9:30 

主讲人：孙亮讲师英国阿尔斯特大学

主持人：高曙明教授浙江大学

1）报告题目：Geometry handling and mesh generation

摘要：为进一步提高仿真精度，飞机、发动机等产品需要在整机模型尺度（包含上千个组件）进行多学科仿真，但从设计的CAD模型到生成可用于仿真分析的CAE模型需要大量的准备时间，这个过程通常伴随大量的手动工作。在这个报告中，我将介绍我在几何模型处理以及网格生成方面的一些工作，主要包括薄壁件自动分解生成六面体为主体网格、虚拟分解以及具有块结构四边形网格生成。

2）授课题目：Introduction to flight

摘要：在21世纪的今天，我们对飞行已经不再陌生。那从最初对飞行的渴望到如今的习以为常，人类都经过了哪些尝试呢？在这个课程中，我将简单的介绍飞行历史以及如何实现飞行。

个人简介：孙亮博士，讲师，目前任职于英国阿尔斯特大学计算工程与智能系统学院。主要研究方向为计算机辅助设计（CAD）与计算机辅助工程（CAE）。2017年博士毕业于英国贝尔法斯特女王大学。2017-2019年在贝尔法斯特女王大学从事博士后研究。参与由Innovate UK和英国国家自然科学基金赞助的课题2项。开发了一系列用于几何处理，几何优化，网格生成和变形的程序。开发的薄壁件自动分解生成六面体为主体的网格的算法在若干工业模型上得到了很好的结果, 相关论文获第25届国际网格生成圆桌会议最佳学生论文奖。

第二场：10:00—11:00 

主讲人：高希峰助理教授弗罗里达州立大学

主持人：黄劲教授  浙江大学

1）报告题目：Robust Meshing

摘要：Simulations with high fidelity play an essential role in many disciplines, such as computer graphics and computer-aided engineering. For more than 30 years, volumetric meshing, i.e. discretizing the interior of an object, has been the bottleneck of high- fidelity simulations. In practice, a large amount of time is spent on manually creating and repairing meshes. In this talk, I propose the first fully robust solution to generate volumetric meshes to meet different requirements for simulations, which were elusive for several decades. The solution is designed to automatically generate and process high-quality structured (hexahedral) meshes, semi-structured (hexahedral-dominant) meshes, and unstructured (tetrahedral) meshes. The datasets and source codes of my research projects are publicly accessible for people from both academic institutes and companies.

2）授课题目：3D Surface Reconstruction

摘要：Meshes created from point clouds by 3D reconstruction methods have wide applications in computer graphics, reverse engineering, and computer vision. Among the many solutions, implicit surface reconstruction is the most effective one for handling point clouds with artifacts. In this class, we will introduce the 3D surface reconstruction problem and go through every step of the standard implicit reconstruction pipeline. By the end of the class, students are expected to fully understand the signed distance function based implicit reconstruction algorithm and should be able to implement it in weeks using C++ programming.

个人简介：Xifeng Gao is an assistant professor at the Computer Science Department of Florida State University. He was a postdoc in the Courant Institute of Mathematical Sciences at New York University. He received his PhD degree in 2016 and won the best PhD dissertation award from the Department of Computer Science at the University of Houston. His research interests are geometry processing, computationally design and fabrication, computer graphics, and robotics. His research works have been published in several leading Journals and conferences, e.g., ACM TOG, IEEE TVCG, ICRA and IROS.