报告人：Eduard Gröller

题目：Scalable Interactive Visual Analysis

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摘要：Scalable Interactive Visual Analysis combines computer-supported, interactive, visual representations of (abstract) data with automatic techniques to amplify cognition and facilitate modeling. In recent years data complexity concerning volume, veracity, velocity, and variety has increased considerably. This is due to new data sources as well as the availability of uncertainty, error, and tolerance information. Instead of individual objects entire sets, collections, and ensembles are visually investigated. There is a need for visual analysis and modelitics as well as, comparative visualization, quantitative visualizations, scalable visualizations, and linked/integrated views. The concepts will be illustrated with various examples from scalable visualization, uncertainty visualization, guided interaction, and immersive analytics. The talk will outline future research directions concerning Scalable Interactive Visual Analysis, e.g., modelitics, biologization of the digital world, fata (future data), immersive analytics, self-adaptive self-explanatory analysis.

个人简介：Eduard Gröller (http://www.cg.tuwien.ac.at/staff/EduardGroeller.html) is Full Professor at the Institute of Visual Computing & Human-Centered Technology (VC&HCT), TU Wien. In 1993 he received his PhD from the same university. His research interests include computer graphics, visualization, and visual computing. He is heading the Research Unit Computer Graphics and the Visualization Group at VC&HCT. The group performs basic and applied research projects in all areas of visualization (http://www.cg.tuwien.ac.at/research/vis/). Dr. Gröller has given lecture series on visualization at various other universities (Tübingen, Graz, Praha, Bahia Blanca, Magdeburg, Bergen). He is a scientific proponent and key researcher of the VRVis research center (http://www.vrvis.at/). The center performs applied research in visualization, rendering, and visual analysis. Dr. Gröller is adjunct professor of computer science at the University of Bergen, Norway (since 2005). He co-authored more than 300 scientific publications and acted as a reviewer for numerous conferences and journals in the field. He also has served and serves on various program and paper committees. Examples include Computers&Graphics, IEEE Transactions on Visualization and Graphics, EuroVis Conference, IEEE Visualization Conference, Eurographics Conference. He has been paper co-chair of Volume Graphics 2005, IEEE Visualization 2005 and 2006, and Eurographics 2006. He has been co-chair of the VisSym 1999 Symposium, the Eurographics 2011 Conference, and the EuroVis 2012 Conference. Dr. Gröller took on the task of area co-chair for IEEE Visualization 2021 and 2022. He has been Chief Editor of the Journal Computer Graphics Forum (http://wileyonlinelibrary.com/journal/cgf) in the period 2008-2011. Dr. Gröller became a fellow of the Eurographics Association in 2009. He is the recipient of the Eurographics 2015 Outstanding Technical Contributions Award and of the IEEE VGTC 2019 Technical Achievement Award.

报告人：Rebecca Ruige Xu

题目：Harnessing the Power of AI in Creative Fields: A Dive into Tools, Biases, Limitations, and Opportunities

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摘要：The rise in AI-generated content has been largely attributed to popular tools such as ChatGPT, Stable Diffusion, and Midjourney. It’s crucial for artists, designers, researchers, and developers to fully comprehend how these tools were developed and the potential biases introduced from their training datasets and fine-tuning procedures. Knowledge of the design philosophy and underlying mechanisms is key for us to effectively assess whether these tools are apt for specific creative tasks or data visualization projects and how these tools should be used responsively to produce reliable results and honestly reflect our artistic intentions. Our focus should extend beyond the limited results and aesthetics yielded by pre-trained models. Seeking more trustworthy data sources that respect copyright laws and appropriately address cultural values is important. Instead of riding a wave blindly, it is better to broaden our perspectives, think critically and engage in meaningful work that harnesses the power of AI in creative fields.

个人简介：Rebecca Ruige Xu teaches computer art as a Professor in the College of Visual and Performing Arts at Syracuse University. Her research interests include artistic data visualization, experimental animation, visual music, interactive installations, digital performance, and extended reality. Xu’s work has appeared at many international venues including IEEE VIS Arts Program; SIGGRAPH & SIGGRAPH Asia Art Gallery; ISEA; Ars Electronica; Museum of Contemporary Art, Italy; Los Angeles Center for Digital Art, etc. Xu is the co-founder of China VIS Arts Program. Currently she serves as the Chair of ACM SIGGRAPH Digital Arts Committee and IEEE VIS’23 Arts Program Co-Chair.