讲者：Dr. Torsten Möller, University of Vienna, Austria, Professor
    题目：Visual tools for understanding multi-dimensional parameter spaces
    摘要：Simulations are an integral part of computational science. Simulations are characterized by a particular set of inputs and a multitude of outputs. Understanding the dependency of the outputs from the inputs is a key for understanding the underlying phenomena that are being modeled. In this talk I will try to give a characterization of such general input/output systems and present several tools we have built to aid in different applications, ranging from fisheries science to medical imaging to fluid simulation. I will try to make the case that visual support greatly facilitates the understanding of these complex systems.
    个人简历：Torsten Moeller is a professor at the University of Vienna, Austria, since 2013. Between 1999 and 2012 he served as a Computing Science faculty member at Simon Fraser University, Canada. He received his PhD in Computer and Information Science from Ohio State University in 1999 and a Vordiplom (BSc) in mathematical computer science from Humboldt University of Berlin, Germany. He is a senior member of IEEE and ACM, and a member of Eurographics. His research interests include algorithms and tools for analyzing and displaying data with principles rooted in computer graphics, human-computer interaction, image processing, machine learning and visualization.
He heads the research group on Visualization and Data Analysis. He served as the appointed Vice Chair for Publications of the IEEE Visualization and Graphics Technical Committee (VGTC) between 2003 and 2012. He has served on a number of program committees and has been papers co-chair for IEEE Visualization, EuroVis, Graphics Interface, and the Workshop on Volume Graphics as well as the Visualization track of the 2007 International Symposium on Visual Computing. He has also co-organized the 2004 Workshop on Mathematical Foundations of Scientific Visualization, Computer Graphics, and Massive Data Exploration as well as the 2010 Workshop on Sampling and Reconstruction: Applications and Advances at the Banff International Research Station, Canada. He is a co-founding chair of the Symposium on Biological Data Visualization (BioVis). In 2010, he was the recipient of the NSERC DAS award. He received best paper awards from IEEE Conference on Visualization (1997), Symposium on Geometry Processing (2008), EuroVis (2010), and ACM Intelligent User Interfaces (IUI, 2016), as well as two second best paper awards from EuroVis (2009, 2012). In 2016 he received the Teaching Award from the University of Vienna.

    讲者：袁晓如 北京大学，研究员
    题目：城市数据可视分析
    摘要：在大数据时代，拥有大量的数据并不等于获得相应价值。和其他分析手段不同，可视化和可视分析利用人类视觉认知的高通量特点，通过图形和交互的形式表现信息的内在规律及其传递、表达的过程，充分结合人的智能和机器的计算分析能力，是人们理解复杂现象，诠释复杂数据的重要手段和途径。可视分析通过将人的因素积极引入分析过程，提供了处理复杂大数据的新的途径。在数据数量越来越大，内容越来越复杂的情况下，可视化的数据交互将成为关键的技术和工具。在这个报告中我们将介绍可视分析的最新发展以及在包括交通、社会媒体、安全领域等城市大数据可视化的工作案例。
    个人简介：袁晓如，研究员，北京大学机器感知与智能教育部重点实验室、信息科学中心、智能科学系副主任，北京大学科学研究部副部长。2006年8月获美国明尼苏达大学计算机科学博士学位。在高维数据、时空轨迹、社会媒体、网络安全数据、复杂流场数据等可视化与可视分析领域开展了系统的工作，发展了一系列多维、时空数据交互分析的方法和工具。在IEEE VIS, IEEE TVCG等重要国际可视化会议以及期刊上发表70余篇文章。高动态范围可视化的工作获得2005年IEEE Visualization大会最佳应用论文奖。多次在IEEE VIS可视化大会 VAST Challenge 可视分析竞赛获奖。担任IEEE VIS，EuroVis, IEEE PacificVis等国际可视化会议程序委员会委员等工作。共同创建中国可视分析大会。2012-1013年CCF YOCSEF 学术委员会主席。其他信息参见http://vis.pku.edu.cn/wiki