报告题目：First Steps Toward Black-Box Finite Element Analysis
报告讲者：Daniele Panozzo, Courant Institute of Mathematical Sciences, New York University, USA
报告摘要：The numerical solution of partial differential equations (PDE) is ubiquitous in computer graphics and engineering applications, ranging from the computation of UV maps and skinning weights, to the simulation of elastic deformations, fluids, and light scattering. Ideally, a PDE solver should be a “black box”: the user provides as input the domain boundary, boundary conditions, and the governing equations, and the code returns an evaluator that can compute the value of the solution at any point of the input domain. This is surprisingly far from being the case for all existing open-source or commercial software, despite the research efforts in this direction and the large academic and industrial interest. To a large extent, this is due to treating meshing and FEM basis construction as two disjoint problems.
I will present an integrated pipeline, considering meshing and element design as a single challenge, that makes the tradeoff between mesh quality and element complexity/cost local, instead of making an a priori decision for the whole pipeline. I will demonstrate that tackling the two problems jointly offers many advantages, and that a fully black-box meshing and analysis solution is already possible for heat transfer and elasticity problems.
讲者简介：Daniele Panozzo is an Assistant Professor of Computer Science at the Courant Institute of Mathematical Sciences in New York University. Prior to joining NYU he was a postdoctoral researcher at ETH Zurich (2012-2015). He earned his PhD in Computer Science from the University of Genova (2012) and his doctoral thesis received the EUROGRAPHICS Award for Best PhD Thesis (2013). Daniele’s research interests are in digital fabrication, geometry processing, architectural geometry and discrete differential geometry. He received the EUROGRAPHICS Young Researcher Award in 2015, the NSF CAREER Award in 2017, and his work has been covered by Swiss National Television and various national and international printed media. Daniele is leading the development of libigl (https://github.com/libigl/libigl), an award-winning (EUROGRAPHICS Symposium of Geometry Processing Software Award, 2015) open-source geometry processing library that supports academic and industrial research and practice. Daniele is chairing the Graphics Replicability Stamp (http://www.replicabilitystamp.org), which is an initiative to promote reproducibility of research results and to allow scientists and practitioners to immediately beneﬁt from state-of-the-art research results.
报告题目：Data Consolidation, Structuralization and Reconstruction
报告摘要：Data consolidation, structuralization and reconstruction are long standing problems, not only in the field of computer graphics, but everywhere. In this talk, I would like to share you a serial of our research along this line, hopefully to be inspiring.
讲者简介：HUI HUANG (黄惠) is a Distinguished Professor of Shenzhen University, where she found and directs the Visual Computing Research Center (VCC). She received her PhD degree in Applied Math from University of British Columbia in 2008 and another PhD degree in Computational Math from Wuhan University in 2006. Her research interests are in Computer Graphics, Vision and Computing, focusing on Geometric Modeling, Shape Analysis, Point Computation, Image Processing, 3D/4D Acquisition and Creation. She is currently an Associate Editor-in-Chief of The Visual Computer (TVC) and is on the editorial board of Computers & Graphics
(CAG) and Frontiers of Computer Science (FCS). She has served on the program committees of many major international conferences including SIGGRAPH ASIA, EG, EG-STAR, SGP, PG, 3DV, CGI, GMP, SMI, SPM, GI,CAD/Graphics, etc. She is invited to be CHINAGRAPH 2018 Program Vice Chair, in addition to SIGGRAPH ASIA 2017 Technical Briefs and Posters Co-Chair, SIGGRAPH ASIA 2016 Workshops Chair and SIGGRAPH ASIA
2014 Community Liaison Chair. She is the recipient of NSFC Excellent Young Scientist and Guangdong Technological Innovation Leading Talent Award. She is also selected as CCF Distinguished Member and ACM/IEEE Senior Member.
讲者简介：缪永伟，博士，教授，博士生导师。系中国工业与应用数学学会几何设计与计算专业委员会常务委员，中国计算机学会计算机辅助设计与图形学专业委员会委员，中国图象图形学学会视觉大数据专业委员会委员。曾赴瑞士、美国、日本、新加坡、以色列、中国香港等地访学或参加学术会议交流；其中于2008年2月至2009年2月赴瑞士University of Zurich (苏黎世大学) 信息学院进行访问学者研究，于2011年11月至2012年5月赴美国University of Maryland (马里兰大学) 计算机科学系进行高级访问学者研究，于2015年7月至2015年8月作为访问教授赴日本University of Tokyo (东京大学) 计算机系进行学术交流和合作研究。主要从事计算机图形学与计算机辅助设计、虚拟现实与人机交互、计算机视觉等方面的研究。在科学出版社出版学术专著1部。研究成果已在国内外重要学术期刊和重要学术会议上正式发表，共发表科研论文100余篇，其中SCI/EI索引论文50余篇，主持或参与国家自然科学基金项目5项，主持省部级项目4项。授权国家发明专利5项。
报告讲者：Xifeng Gao - New York University, Florida State University, USA
报告摘要：While knitted garments are common in our daily lives, designing knitting patterns digitally for a given 3D surface remains a challenge. In practice, it requires a high level of expertise and numerous iterations of trial and error to figure out how to knit a particular 3D shape. In this talk, I will introduce a fully automatic pipeline that converts a given arbitrary 3D shape into a knit structure. The pipeline begins with re-meshing that produces a quad-dominant mesh from the input shape. Then, the edge labels of the mesh and the knitting directions over the surface are determined using a two-step global optimization process. Finally, a valid stitch mesh can be generated, which can be used to produce the final yarn-level model. The effectiveness of the introduced pipeline is verified by producing knit models from complex 3D shapes, producing stitch meshes from a large collection of arbitrary models, and 3D printing our final yarn-level models.
讲者简介：Xifeng Gao is now holding a PostDoc position at the Courant Institute of Mathematical Sciences of New York University. Dr. Gao will join the Department of Computer Science at FSU in Fall 2018 as an Assistant Professor. He received his Ph.D. degree in 2016 and won the best Ph.D. dissertation award from the Department of Computer Science at the University of Houston. Dr. Gao has wide research interests that are related to geometry processing, such as Computer Graphics, Visualization, Multimedia Processing, Medical Imaging, Information Forensics, and Digital Fabrication. His research works have been published in several leading Journals, e.g., ACM TOG, ACM TOMM, CGF, and IEEE TVCG. More details about his research can be found on his homepage.
讲者简介：舒振宇，副教授，分别于2002年、2005年和2010年获得浙江大学应用数学学士、硕士和博士学位。2015年至2016年期间担任美国犹他大学计算机学院图形学实验室访问学者。现为浙江大学宁波理工学院数据工程与计算科学研究所副所长、中国工业与应用数学学会几何设计与计算专委会委员，中国计算机学会计算机辅助设计与图形学专委会委员。目前主要从事计算机图形学，数字几何处理等领域的研究工作，已在包括《ACM Transactions on Graphics》、《ACM CHI Conference on Human Factors in Computing Systems》、《Computer-Aided Design》、《Computer Aided Geometric Design》等在内的各类学术期刊和会议上发表或录用了相关论文30篇，主持完成了国家自然科学基金1项、浙江省自然科学基金2项，宁波市自然科学基金4项，参与完成了4项国家自然科学基金的研究工作。