2021 PKU International Visualization Summer School
The 12th PKU International Visualization Summer School will be held from
July 14 to 22, 2021. The summer school invites
well-known scholars at home and abroad with profound knowledge in the field of visualization
research. In combination with the advanced visualization technology, they teach the basic knowledge
of visualization technology, and systematically discuss the cutting-edge theories and research
methods in this field for students. From July 14 to 16, is the elementary course, which
focuses on the fundamentals of visualization techniques and design. From July 17 to 22, is the
advanced course.
Organized by
Key Laboratory of Machine Perception (Ministry of Education)
National Engineering Laboratory for Big Data Analysis and Application
The summer school focuses on recruiting graduate students and doctoral students in visualization related fields. At least 1/6 of the formal students will have a design background. The course design will assign students with technical and design backgrounds to collaborate. Those who pass the course design assessment will receive a 4-credit certificate of completion of the summer school issued by Graduate School of Peking University.
Audit application are also enrolled. After completing the course questionnaire and corresponding tasks through online listening, they will be listed on this website to prove their participation in the course. Due to the university's epidemic prevention regulations, only students in PKU will be able to attend the course offline. For the time being, all formal and audit students from outside the university will attend classes online.
The selection of students is based on a free application and merit-based approach. Letters of recommendation from a mentor or supervisor are required to enroll as a former student. The application materials will be reviewed by the expert committee to decide the admission list. Students with master's or doctoral degrees and young faculty members from universities and research institutes in China in related fields, as well as those engaged in R&D in enterprises, are eligible to apply. The summer school also encourages a small number of outstanding senior undergraduates who have a strong interest in the field of visualization and are interested in applying for graduate studies at Peking University to attend the program. Please indicate the relevant information in your application.
Free.
Registration for students: http://www.chinavis.org/s21/register/index_en.html
For registration, please fill in the required information on the page
for submitting application materials, and ask the recommender(s) (two persons for formal application
and one person for audit application) to send the
recommendation letter to pkuvis@pku.edu.cn to complete the application. Applicants who have been
approved by the expert committee will be notified. If the information is incomplete or the
recommendation letters are not received, the application is invalid.
The deadline for summer school registration is June 20th. The
admission notice will be sent to the applicant's registered mailbox in batches.
| Date | Time | Speaker | Content |
|---|---|---|---|
| July 14 | 14:00-15:30 | Xiaoru Yuan | Openning Session |
| 15:45-17:15 | Xiaoru Yuan | Basics of Visualization | |
| 19:00-20:15 | Rebecca Xu | Introduction to Data Art & Visualization Design | |
| 20:30-21:30 | Rebecca Xu | Concept-Driven Design Process and Fundamental Artistic/Design Principles | |
| July 15 | 12:00-14:00 | Xiaoru Yuan/Rebecca Xu | Project Design Preview |
| 19:00-20:15 | Rebecca Xu | Developing Visual Design and Presentation | |
| 20:30-21:30 | Rebecca Xu | Understanding Audiences and the Role of Design with Data | |
| July 16 | 14:00-15:30 | Xiaoru Yuan | Design Space of Visualization Technology |
| 15:45-17:15 | Xiaoru Yuan | Design Space of Visualization Technology | |
| 19:00-20:15 | Rebecca Xu | Data Storytelling; Design Best Practices | |
| 20:30-21:30 | Rebecca Xu | Visualization Testing; Collaboration in Visualization | |
| July 17 | 14:00-15:00 | Chen Siming, Zeng Wei, Tao Jun | Panel |
| July 19 | 8:30-10:00 | Zhicheng Liu | 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) | |
| July 20 | 8:30-10:00 | Zhicheng Liu | 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? | |
| July 21 | 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 | |
| July 22 | 8:30-10:00 | Xiaoru Yuan/Rebecca Xu | Project Presentation |
| 10:15-11:45 | Xiaoru Yuan/Rebecca Xu | Project Presentation | |
| July 26 | Project Presentation at ChinaVis |
Abstract : This lecture introduces the basics of visualization.
Abstract : 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.
Abstract : This lecture introduces the design space of visualization technology.
Abstract : 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.
Abstract : 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.
Abstract : In this talk, Remco Chang will introduce interactive machine learning and analysis of user interactions (analytic provenance).
Abstract : 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.
Abstract : 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.
Abstract : 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.
Abstract : This session introduces multidimensional multivariate visualization.
Abstract : This session introduces network visualization.
Abstract : 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.
Xiaoru Yuan
Speaker Introduction: Xiaoru Yuan is a professor at the School of Electronics Engineering and Computer Science, Peking University, a PhD supervisor, deputy director of Key Laboratory of Machine Perception (Ministry of Education), and executive deputy director of National Engineering Laboratory for Big Data Analysis and Application. At the beginning of 2008, he established the Visualization and Visual Analytics Laboratory at Peking University. His research directions include complex field data visualization, high-dimensional/spatial-temporal data visualization, traffic and social data analysis and rapid construction methods of visualization. The work of high dynamic range visualization won the Best Application Paper Award in IEEE VIS 2005. Since 2013, he has guided the laboratory team to win 7 prizes in the IEEE VAST challenge. He has served dozens of times as a member of the IEEE VIS, EuroVis, IEEE PacificVis and other international visualization conference procedure committee. He was the papers co-chair for IEEE VIS 2017 (SciVis), and he involved in creating ChinaVis. He is director of the China Computer Federation, distinguished member, distinguished speaker. He is member of Big Data Committee, menber of Human-Computer Interaction Standing Committee and member of Computer Aided Design and Graphics Committee of China Computer Federation. He is the director of China Society of Image and Graphics, director of Visualization and Visual Analysis Committee.
Rebecca Ruige Xu
Speaker Introduction: Rebecca Ruige Xu's artwork and research interests include artistic data visualization, visual music, experimental animation, interactive installations, digital performance and virtual reality. Her recent work has been 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; Boston Cyberarts Festival, USA. Xu currently teaches computer art and animation in College of Visual and Performing Arts at Syracuse University.
Remco Chang
Speaker Introduction: 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
Speaker Introduction: 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 awards 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
Speaker Introduction: 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
Speaker Introduction: 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.
Zhicheng Liu
Speaker Introduction: 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
Speaker Introduction: 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.
