课程信息

    第十二期2021年北京大学可视化发展前沿研究生暑期学校将于2021年7月14日-22日举行。

    可视化暑期学校邀请海内外在可视化研究领域具有深厚造诣的知名学者,面向学员系统探讨本领域的前沿理论和研究方法。2021年7月14日-16日为可视化基础课程部分,该部分课程主要讲授可视化技术与设计基础。2021年7月17日-22日为前沿课程。

    承办单位
    北京大学机器感知与智能教育部重点实验室
    北京大学大数据分析与应用技术国家工程实验室

招生信息

正式学员

暑期学校重点招收可视化相关方向硕士研究生、博士研究生。报名需要有推荐人的推荐信。正式学员中至少1/6为设计背景。课程设计将分配技术与设计背景共同完成。完成课程设计考核合格者,可获得北京大学研究生院颁发的4学分暑期学校结业证书。

非正式学员

同时招收非正式学员,通过在线听课完成课程调查问卷和相应任务后,将在网站列出名单,证明参与课程。由于学校防疫规定,仅本校学生在线下听课。外校同学,正式学员或者非正式学员,暂时均通过在线上课。

学员选拔

学员选拔采取自由报名,择优录取的方式。报名材料由专家委员会审查后决定录取名单。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,或者企业从事相关研发人员均可申请。暑期学校同时鼓励少量对可视化领域有浓厚兴趣,有志于申请北京大学研究生的优秀高年级本科生参加学习,请在申请时注明相关信息。

学费标准

    本次暑期学校不收取学费。

提交申请材料

    申请提交信息与材料页面:http://www.chinavis.org/s21/register/index.html
    请在提交申请材料页面填写所需信息。正式学员申请需要两份推荐信,非正式学员申请需要一份推荐信。请推荐人将推荐信发送至邮箱pkuvis@pku.edu.cn。经专家委员会审核通过后,将会收到邮件通知。
    暑期学校报名截止日期为6月20日,录取通知会分批发送至注册时提交的电子邮箱中。

日程安排

日期 时间 讲者 内容
7月14日 14:00-15:30 袁晓如 开幕式
15:45-17:15 袁晓如 可视化基础
19:00-20:15 徐瑞鸽 Introduction to Data Art & Visualization Design
20:30-21:30 徐瑞鸽 Concept-Driven Design Process and Fundamental Artistic/Design Principles
7月15日 12:00-14:00 袁晓如/徐瑞鸽 课程设计预览
19:00-20:15 徐瑞鸽 Developing Visual Design and Presentation
20:30-21:30 徐瑞鸽 Understanding Audiences and the Role of Design with Data
7月16日 14:00-15:30 袁晓如 可视化技术设计空间
15:45-17:15 袁晓如 可视化技术设计空间
19:00-20:15 徐瑞鸽 Data Storytelling; Design Best Practices
20:30-21:30 徐瑞鸽 Visualization Testing; Collaboration in Visualization
7月17日 14:00-15:00 陈思明、曾伟及陶钧 圆桌会议
7月19日 8:30-10:00 刘志成 Visualization Design
10:15-11:45 Tim Dwyer Network Visualization
19:00-20:15 Remco Chang Interactive Machine Learning
20:30-21:30 Remco Chang Analysis of User Interactions (Analytic Provenance)
7月20日 8:30-10:00 刘志成 Visualizing Event Sequence Data
10:15-11:45 Tim Dwyer Immersive Analytics
19:00-20:15 Jian Chen Intelligent Augmentation
20:30-21:30 Jian Chen What Can Tables Tell Us About Data?​
7月21日 8:30-10:00 Michael McGuffin Multidimensional Multivariate Visualization
10:15-11:45 Michael McGuffin Network Visualization
19:00-20:15 Benjamin Bach Storytelling + Data Comics
20:30-21:30 Benjamin Bach Storytelling + Data Comics
7月22日 8:30-10:00 袁晓如/徐瑞鸽 课程项目展示
10:15-11:45 袁晓如/徐瑞鸽 课程项目展示
7月26日 ChinaVis课程项目展示

课程内容


    授课题目: 可视化基础
    讲者: 袁晓如, 北京大学
    时间: 7月14日 15:45 - 17:15

课程摘要 : 本课程讲授可视化的基础。


    授课题目: Visual Design Fundamentals and Considerations in Data Visualization
    讲者: 徐瑞鸽,雪城大学
    时间: 7月14日-16日 19:30 - 21:30

课程摘要 : This course explores a concept-driven process and method for creating expressive and effective visualizations. Coupled with a few hand-on exercises, we’ll cover generating suitable, exciting concepts and ideas for visualization; developing and selecting appropriate, effective presentation; designing and enhancing the aesthetics and impact of final outcome. Basic visual design process and fundamental principles in information visualization will be included. We will also broadly discuss how to use data visualization as a means for communicating ideas and stories through reviewing various methods and approaches for visualizing data. This course aims to help both data researchers and artists/designers enhance their artistic knowledge and perceptions, expand their approaches to expressive and effective visualizations, hopefully to achieve a balance among aesthetic quality, design-thinking and statistical rigor in their work.


    授课题目: 可视化技术设计空间
    讲者: 袁晓如, 北京大学
    时间: 7月16日 14:00 - 17:15

课程摘要 : 本课程探讨可视化技术的设计空间。


    授课题目: Visualization Design
    讲者: 刘志成,美国马里兰大学
    时间: 7月19日 8:30 - 10:00

课程摘要 : This lecture will cover fundamental issues related to visualization design. We will review definitions of design in the HCI literature and the objectives of design in InfoVis. Then we will discuss visualization design methods and models. Finally we will talk about current research on visualization design and authoring tools.


    授课题目: Network Visualization
    讲者: Tim Dywer,蒙纳士大学
    时间: 7月19日 10:15 - 11:45

课程摘要 : In this talk, Tim Dwyer will reflect on his research network visualisation and the potential of network visualisation to help people to better understand a connected world.


    授课题目: Interactive Machine Learning + Analysis of User Interactions (Analytic Provenance)
    讲者: Remco Chang,塔夫茨大学
    时间: 7月19日 19:00 - 21:30

课程摘要 : In this talk, Remco Chang will introduce interactive machine learning and analysis of user interactions (analytic provenance).


    授课题目: Visualizing Event Sequence Data
    讲者: 刘志成,美国马里兰大学
    时间: 7月20日 8:30 - 10:00

课程摘要 : This lecture will cover concepts, visualization techniques and visual analytics approaches for event sequence data. We start with terminology, examples and tasks for event sequences. Then we introduce visualization techniques for such data. Finally we will discuss approaches that combine visual interfaces with automated algorithms for event sequence analysis.


    授课题目: Immersive Analytics
    讲者: Tim Dywer,蒙纳士大学
    时间: 7月20日 10:15 - 11:45

课程摘要 : In this talk, Tim Dwyer will discuss his more recent work in the area of Immersive Analytics, which aims to bring data out of computer centres and into the world around us.


    授课题目: Recent Advances in Teaching Machines to Understand Visualizations
    讲者: Jian Chen,俄亥俄州立大学
    时间: 7月20日 19:00-21:30

课程摘要 : Convolutional neural network's graphical reading is an emergent area of research to study the machine's ability to visually decoding of information encoded in images containing visualizations. A variety of visualization tasks, benchmarked over visual imagery have driven tremendous progresses in using intelligent machine to aid human's tasks. This tutorial will focus on some of the recently popular tasks in this area such as document understanding, graphical perception, captioning, and visual question answering. We will cover state-of-the-art approaches in each of these areas and discuss key principles that epitomize the core challenges and opportunities in image understanding, extraction, and comparative studies of human and machine's intelligence.


    授课题目: Multidimensional Multivariate Visualization
    讲者: Michael McGuffin,高等技术学院(ETS)
    时间:7月21日 8:30 - 10:00

课程摘要 : This session introduces multidimensional multivariate visualization.


    授课题目: Network Visualization
    讲者: Michael McGuffin,高等技术学院(ETS)
    时间: 7月21日 10:15 - 11:45

课程摘要 : This session introduces network visualization.


    授课题目: Storytelling + Data Comics
    讲者: Benjamin Bach,爱丁堡大学
    时间: 7月21日 19:00 - 21:30

课程摘要 : This session introduces into the visual data-driven storytelling. It discusses how to effectively create stories around data and communicate them through a set of media (videos, infographics, comics, etc.). The first part of the session will be a high-level overview over concepts and examples in data-driven storytelling. The second part will be a step-by-step guide to create a storyboard for your own data stories. During this guide, the session will provide activities and time to work in break-out groups on your own projects. No reparation is required for this session. The only material necessary are sheets of paper and simple pens to participate in the sketching sessions.

暑期学校讲者简介

    袁晓如
    北京大学

讲者简介 : 袁晓如博士是北京大学信息科学与技术学院研究员,博士生导师,机器感知与智能教育部重点实验室副主任,大数据分析与应用国家工程实验室常务副主任。2008年初在北京大学建立可视化与可视分析实验室,研究方向包括复杂流场数据可视化,高维/时空数据,交通、社会媒体数据的分析,可视化的快速构建方法。高动态范围可视化的工作获得2005年IEEE VIS大会最佳应用论文奖。2013年来指导实验室团队7次在IEEE VAST可视化分析挑战赛中获奖。数十次担任IEEE VIS, EuroVis, IEEE PacificVis等国际可视化会议程序委员会委员,2017年 IEEE VIS大会论文共同主席(SciVis),创建中国可视化与可视分析(ChinaVis)大会。中国计算机学会理事,杰出会员,杰出讲者。中国计算机学会大数据专家委员会委员,人机交互专委会常务委员和计算机辅助设计与图形学专委会委员。中国图象图形学学会理事、可视化与可视分析专业委员会主任。


    徐瑞鸽
    雪城大学

讲者简介 : Rebecca Ruige Xu currently teaches computer art as a Professor in College of Visual and Performing Arts at Syracuse University. Her artwork and research interests include artistic data visualization, experimental animation, visual music, interactive installations, digital performance, and virtual reality. Her recent work has appeared at: IEEE VIS Arts Program; SIGGRAPH & SIGGRAPH Asia Art Gallery; ISEA; Ars Electronica; Museum of Contemporary Art, Italy; Los Angeles Center for Digital Art, USA; FILE– Electronic Language International Festival, Brazil; Techfest -Technical Arts Exhibition, India; Colloquium culture and digitization, Switzerland; CYNETart, Germany; International Digital Art Exhibition, China. Xu served on the Media Arts Advisory Panel for the U.S. National Endowment for the Arts, was the Co-Chair for 2019, 2021 IEEE PacificVIS Visual Storytelling Contest. She is currently on the Executive Committee for the Association of Chinese Artists in American Academia, and is serving as the Exhibition Chair for 2021 IEEE VIS Arts Program and the Co-Chair for ChinaVIS Conference Arts Program.


    Remco Chang
    塔夫茨大学

讲者简介 : Remco Chang is an Associate Professor in the Computer Science Department at Tufts University. He received his BA from Johns Hopkins University in 1997 in Computer Science and Economics, MSc from Brown University in 2000, and PhD in Computer Science from UNC Charlotte in 2009. Prior to his PhD, he worked for Boeing developing real-time flight tracking and visualization software, followed by a position at UNC Charlotte as a research scientist. His current research interests include visual analytics, information visualization, HCI, and databases. His research has been funded by the NSF, DARPA, Navy, DOD, the Walmart Foundation, DHS, MIT Lincoln Lab, and Draper. He has had best paper, best poster, and honorable mention awards at InfoVis, VAST, CHI, and VDA and was one of the program chairs of the IEEE VIS conference in 2018 and 2019. He is currently an associate editor for the ACM TiiS journal and the IEEE TVCG journal. He received the NSF CAREER Award in 2015. He has supervised a number of PhD students and postdocs who became professors in Computer Science (at Smith College, DePaul, Washington University in Saint Louis, University of Maryland, University of San Francisco, Bucknell, WPI, San Francisco State, the University of Utrecht, and Northeastern) and in industry research (Google, Facebook, MIT Lincoln Lab, Draper, and Novartis).


    Tim Dwyer
    蒙纳士大学

讲者简介 : Tim Dwyer is Australia’s foremost Information Visualisation researcher with 18 papers at the premier conference for this discipline, CORE A*-ranked IEEE InfoVis. He also has publications on topics in data visualisation, visual analytics and human computer interaction in ACM CHI, ACM UIST, IEEE VAST, IEEE PacificVis, EuroVis, Interact, Graph Drawing, Diagrams, IEEE TVCG, WWW and others. He has over 80 papers total, with over 3,000 citations and an h-index of 33. He has received two best paper and one Honourable Mention for best paper award at the IEEE VIS Conference, as well as best-paper awards at IEEE PacificVis and IEEE BDVA. In 2018 and 2019 he was recognised in The Australian newspaper Research Magazine as Australia’s foremost Computer Graphics researcher based on his publications in premier computer graphics journals. His work combines expertise in algorithms, optimisation and interaction design and evaluation. His career has spanned industry as well as academia and he has developed techniques for network visualisation, set visualisation and multidimensional scaling that have seen practical application in numerous software projects, including Microsoft Visual Studio.


    Michael McGuffin
    高等技术学院(ETS)

讲者简介 : Michael McGuffin is a professor at ETS, a French-language engineering school in Montreal, Canada, where his students conduct research in Human-Computer Interaction (HCI), visualization, virtual reality (VR) and augmented reality (AR). Before joining ETS, he did a Ph.D. at University of Toronto, and before that, he worked as a software developer at a few companies, including Alias|wavefront and Discreet Logic (both now part of Autodesk). In 2009, his paper at the IEEE Information Visualization Conference (InfoVis 2009) received an Honourable Mention for best paper award.


    Jian Chen
    俄亥俄州立大学

讲者简介 : Chen Jian is an associate professor at the Department of Computer Science and Engineering at The Ohio State University. She received PhD degree in Computer Science from Virginia Tech advised by Doug A. Bowman and did postdoctoral work with David H. Laidlaw at Computer Science Department at Brown University. Her research centers around the fascinating interdisciplinary science of interactive visualization and virtual reality. She is directing the OSU Interactive Visual Computing Lab , where she works with the most brilliant students and colleagues worldwide to understand how humans see, make sense, retain, and understand information and to design and study new interactive metaphors and visualization to augment scientists' ability to explore vast amount of data on desktop or immersive virtual environments. Her current methods combine cognitive and perceptual experiments and mathematical modeling.


    刘志成
    马里兰大学

讲者简介 : Zhicheng Liu is an assistant professor in the department of computer science at University of Maryland. Prior to joining UMD in August 2021, he was a research scientist at the Creative Intelligence Lab, Adobe Research. Zhicheng received his PhD in the Human-Centered Computing program from Georgia Tech and was a postdoctoral fellow at the Department of Computer Science of Stanford University. His research on data visualization and human-data interaction has received multiple awards from the ACM CHI and IEEE VIS conferences.


    Benjamin Bach
    爱丁堡大学

讲者简介 : Benjamin is a Lecturer in Design Informatics and Visualization at the University of Edinburgh where he is heading the VisHub research group (https://visualinteractivedata.github.io/). His research designs and investigates interactive information visualization interfaces to help people explore, communicate, and understand data across media such as screens, mixed reality, paper, and physicalizations. Benjamin has beenworking extensively on data-driven storytelling through data comics (datacomics.github.io).Before joining the University of Edinburgh in 2017, Benjamin worked as a postdoc at Harvard University (Visual Computing Group), Monash University, as well as the Microsoft-Research Inria Joint Centre. Benjamin was visiting researcher at the University of Washington and Microsoft Research in 2015. He obtained his PhD in 2014 from the Université Paris Sud where he worked at the Aviz Group at Inria. The PhD thesis entitled Connections, Changes, and Cubes: Unfolding Dynamic Networks for Visual Exploration got awarded an honorable mention as the Best Thesis by the IEEE Visualization Committee. In 2019, Benjamin got awarded the Eurographics Young Researcher Award.

课程设计