课程信息

2016年北京大学
可视化发展前沿研究生暑期学校

     第八期2016年北京大学可视化发展前沿研究生暑期学校将于2016年7月 14 日 - 23 日举行。7月14日-19日的上课地点为北京大学,7月20日-23日将前往长沙参加2016年ChinaVis会议。北京大学可视化发展前沿研究生暑期学校由教育部机器感知与智能重点实验室承办。暑期学校面向全国招生,国内各大院校和研究院所中相关专业的在校硕士、博士研究生和青年教师均可申请,同时可接受少量对可视化领域有浓厚兴趣的优秀高年级本科生。学员参加本项目课程的学习并通过相关的考核将获得由北京大学印制的研究生暑期学校结业证书。本次暑期学校的重点是面向大数据的高性能可视化与可视分析。邀请海内外在可视化研究领域具有深厚造诣的知名学者,面向研究生和青年教师系统探讨本领域的前沿理论和研究方法。
    主办单位:北京大学信息科学技术学院教育部机器感知与智能重点实验室
    课程地点:理科教学楼403
    课程时间:2016年7月14日——2016年7月23日

课程日程

日期 时间 内容 地点
7 月 13 日 14:00-16:00 Student Registration Room216, Science Building #2
(理科二号楼216)
7 月 14 日 09:30-12:30 Summer School Opening (ppt 下载,7.8M)
Xiaoru Yuan, Peking University, Professor
Room 403, Teaching Building
(理教403)
14:00-17:00 Lab Tour Room2306, Science Building #2
(理科二号楼2306)
7 月 15 日 09:30-12:00 Visual tools for parameter exploration – five case studies (ppt 下载,6.7M)
Torsten Möller, University of Vienna, Austria, Professor
Room 403, Teaching Building
(理教403)
14:00-17:00 Visual analytics provenance for sense making (ppt 下载,2.3M)
Kai Xu, Middlesex University, Associate Professor
7 月 16 日 09:30-12:30 Case studies of Visual Analytics for the defence and intelligence analysis (ppt 下载,3.7M)
Kai Xu, Middlesex University, Associate Professor
14:00-17:00 Using Geo-Visualization to Support Sense making (ppt 下载,8.9M;ppt 下载,3.0M)
Xiaolong Zhang, Pennsylvania State University, University Park, Associate Professor
17:00-18:00 Xiaolong Zhang, Xiaoru Yuan, Torsten Möller, Peter Eades – Panel
7 月 17 日 09:30-12:00 大数据时代可视化研究的任务与挑战 (ppt 下载,4.0M)
Xiaoru Yuan, Peking University, Professor
14:00-17:00 The Classical Graph Visualization Methods (ppt 下载,1.7M;ppt 下载,4.4M;ppt 下载,0.9M)
Peter Eades, University of Sydney, Professor
7 月 18 日 09:30-12:00 Visual data science – from examples to abstraction (ppt 下载,7.0M)
Torsten Möller, University of Vienna, Austria, Professor
14:00-17:00 Challenges for Very Large Graph Visualization (ppt 下载,0.2M)
Peter Eades, University of Sydney, Professor
7 月 19 日 09:30-12:00 High-Dimensional Data Visualization and Exploration
Jinwook Seo, Seoul National University, Korea, Associate Professor
14:00-17:00 Evaluations Techniques
Jinwook Seo, Seoul National University, Korea, Associate Professor
7月20日 – 7月23 日 ChinaVis 2016 长沙

课程内容

    Student Registration, Opening Session and Lab Tour
    July 13, 14:00 – 16:00, Student registration, Room 216, Science Building #2 (理科二号楼216)
    July 14, 9:30 – 10:30, Opening Session, Room 403, Teaching Building (理教403)
    July 14 14:00 – 17:00, Lab Tour

    Prof. Torsten Möller – Visual tools for parameter exploration – five case studies
    July 15, 9:00 – 12:00, Room 403, Teaching Building (理教403)
    In this session I would like to present 5 case studies how visual analysis can support the building and the use of computational models. The applications seem at first few rather diverse, but they have strong commonalities. Towards the end we will give a tutorial for one of the tools we have build – VisRseq (see http://visrseq.github.io).

    Prof. Kai Xu – Visual analytics provenance for sense making
    July 15, 14:00 – 17:00, Room 403, Teaching Building (理教403)
    This part discusses what sense making and (visual) analytic provenance are, why they are important in the current context of Big Data, the current research challenges in both areas, and a few recent work on these topics.

    Prof. Kai Xu – Case studies of Visual Analytics for the defence and intelligence analysis
    July 16, 9:00 – 12:00, Room 403, Teaching Building (理教403)
    This session will cover a number of use cases of the development of visual analytics tools and techniques for users within the defence and intelligence analysis community. It will cover some of the unique requirements from this particular community and examples of typical analyses. Each use case will cover the entire development lifecycle, from requirement, design, implementation, to evaluation.

    Prof. Xiaolong Zhang - 用基于地图的可视化方法来支持意义构建
    July 16, 14:00 – 17:00, Room 403, Teaching Building (理教403)
    在日常生活中,对时空数据的分析和理解变得日益主要。本讲座将首先介绍基于地图的可视化的基本概念,然后结合两个科研课题,从意义构建的角度出发,探讨基于地图的可视化方法在团队决策、个人环境认知方面的作用。

    Panel
    July 16, 17:00 – 18:00, Room 403, Teaching Building (理教403)
    Topic: career in visualization

    Prof. Xiaoru Yuan - 大数据时代可视化研究的任务与挑战
    July 17, 9:00 – 12:00, Room 403, Teaching Building (理教403)
    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化与可视分析的最新发展以及在进一步发展中面临的主要任务和挑战。

    Prof. Peter Eades - The Classical Graph Visualization Methods
    July 17, 14:00 – 17:00, Room 403, Teaching Building (理教403)
    We describe some of the classical methods for visualization graphs. These include an orthogonal graph drawing algorithm, the barycentre method, and a simple force-directed approach.

    Prof. Torsten Möller - Visual data science – from examples to abstraction
    July 18, 9:00 – 12:00, Room 403, Teaching Building (理教403)
    On this day I will explain the principle approach on how to conduct this research – through design studies. I will then take an abstraction lense and will highlight the tasks that are all common for the tools presented during the first day. I will also highlight the difference. I will finish in arguing that the major challenge facing us a visualization experts is the support of appropriate modeling approaches, which is the basis of an area I call Visual Data Science.

    Prof. Peter Eades - Challenges for Very Large Graph Visualization
    July 18, 14:00 – 17:00, Room 403, Teaching Building (理教403)
    The classical graph visualization methods create good pictures of small graphs, but do not scale beyond a few hundred nodes and edges. Over the past 20 years, many attempts have been made to create methods to visualize much larger graphs; there have been some successes and many failures. We describe some of these attempts, and consider directions for research in very large graph visualization.

    Prof. Jinwook Seo - High-Dimensional Data Visualization and Exploration
    July 19, 9:00 – 12:00, Room 403, Teaching Building (理教403)
    In this session, we start with fundamental visual perception theories and then move on to some important topics on techniques and challenges regarding high-dimensional data visualization and exploration. The rank-by-feature framework and some other projection-based methods will be covered.

    Prof. Jinwook Seo - Evaluations Techniques
    July 19, 14:00 – 17:00, Room 403, Teaching Building (理教403)
    In this session, we start with fundamental HCI theories and techniques for designing interactive visualization systems, and then move on to various evaluation techniques (qualitative and quantitative). Qualitative techniques include MILCs (Multidimensional In-depth Long-term Case Studies) and some of the techniques related to the design study methodologies by Sedlmair et al.

特邀讲师

    讲者:Peter Eades University of Sydney, Professor
    个人简历:Peter Eades is an Australian computer scientist, a professor in the School of Information Technologies at the University of Sydney, known for his expertise in graph drawing. He received his bachelor's degree in mathematics from Australian National University in 1974, and his Ph.D. in mathematics from the same university in 1977 under the supervision of Jennifer Seberry. He then did postdoctoral studies at the University of Waterloo before taking an academic position at the University of Queensland, where he remained until 1991. He was a professor of computer science at the University of Newcastle from 1992 to 1999, and joined the University of Sydney faculty in 2000. As well as his faculty position at Sydney, Eades is also a distinguished researcher at NICTA.

    讲者:Torsten Möller University of Vienna, Austria, Professor
    个人简介:Torsten Möller 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:Jinwook Seo Seoul National University, Korea, Associate Professor
    个人简介: Jinwook Seo, an associate professor in the Computer Science and Engineering Department at Seoul National University, Korea. He is the first professor who founded an HCI research program in Seoul National University. He is teaching graduate and undergraduate HCI courses and an information visualization course at the graduate level. His research interests include user interface design, interaction design, information visualization and visual analytics. As a director of the Human-Computer Interaction Laboratory at the Department of Computer Science and Engineering, he helps his students find their potentials as young researchers and design their own research goals. Under his guidance, members of the HCI Laboratory perform various research projects derived by their own interests and passions, as well as engage in several interdisciplinary research projects with collaborators in other research fields, industries and government. He received his Bachelor's and master's degree in Computer Science and Engineering from Seoul National University, Korea, and Ph.D in the Human-Computer Interaction Lab at University of Maryland, College Park, USA.

    讲者:Kai Xu Middlesex University, Associate Professor
    个人简介: Kai Xu is an Associate Professor in Data Analytics at the Middlesex University. He has over 15 year experience in data visualisation and analytics research in both the academic and industry context. He has extensive experience working with the UK government departments and leading defence companies in data analytics projects and received over £12 million in total research funding. His work has won a few international data visualisation awards.


    讲者:袁晓如 北京大学,研究员
    个人简介: 袁晓如,北京大学信息科学与技术学院研究员,现任信息科学中心副主任,北京大学学科研究部副部长。博士毕业于美国明尼苏达大学计算机科学系,长期专注于可视化与可视分析的研究,主要研究方向包括科学可视化、信息可视化、可视分析、计算机图形学和人机交互等。针对数据挑战,从理论、方法、应用系统实现多方面开展可视化与可视分析研究。在IEEE Visualization, IEEE Information Visualization, IEEE Visual Analytics Science and Technology (VAST), IEEE TVCG, IEEE EuroVis, IEEE PacificVis等重要国际可视化会议以及期刊上发表70余篇文章。 关于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。IEEE VIS可视化大会VAST Challenge 竞赛五项奖励。担任IEEE VIS, EuroVis, IEEE PacificVis等国际可视化会议程序委员会委员等。创建了中国可视分析大会并担任2014年首届中国可视分析大会程序委员会共同主席。任《计算机辅助设计与图形学学报》,《数值计算与计算机应用》,Journal of Visualization (Springer)等国内外期刊编委,IEEE TVCG,IEEE CG&A 客座编辑。中国计算机学会(CCF)杰出会员,CCF YOCSEF 2012-2013年度主席。其他信息参见http://vis.pku.edu.cn/wiki

    讲者:张小龙 美国宾夕法尼亚州州立大学,副教授
    个人简介: 张小龙,美国宾夕法尼亚州州立大学(The Pennsylvania State University, University Park)的信息科学与技术学院的副教授(Associate Professor),担任宾夕法尼亚州州立知识信息科学与技术学院知识可视化实验室主任。其主要研究领域是计算机人机交互(Human-Computer Interaction),目前在研课题包括多尺度信息可视化理论和系统、社交网络分析和可视化方法和系统、可视化分析中的交互设计与数据处理算法的融合理论和方法、移动设备的交互系统设计和评估等。所承担课题由美国国家科学基金委、阿尔卡特朗讯等机构资助。相关的研究论文发表于International Journal of Human Computer Studies, Journal of Visual Languages and Computing, Presence: Teleoperators and Virtual Environments等国际期刊,以及ACM CHI, ACM UIST, ACM/IEEE JCDL等国际会议。 张博士于清华大学获工学学士(1992)和工学硕士(1994)学位,2003年获美国密歇根大学信息学博士学位。2003年至2005年执教于亚历桑那大学(University of Arizona)。

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