CSIG-VIS International Lecture Series 16
    Prof. Rüdiger Westermann | Neural Network-based Upscaling and Sampling for In-Situ Visualization


    Speaker: Prof. Rüdiger Westermann

    Technical University Munich, Germany.

    Topic: Neural Network-based Upscaling and Sampling for In-Situ Visualization

    Time: May.5, 2022 19:00-20:30 (China Standard Time)

    Abstract: Complementary to the use of classical data compression and spatial as well as temporal subsampling schemes for in situ volume visualization, learning-based approaches have recently emerged as an interesting supplement. Here, upscaling refers to the spatial or temporal reconstruction of a signal from a reduced representation that requires less memory to store and sometimes even less time to generate. The concrete tasks where network-based data condensation and upscaling have been shown to work effectively in visualization are variable-to-variable (V2V) transfer, to predict certain parameter fields from others; upscaling in the data domain, to infer the original spatial resolution of a 3D dataset from a downscaled version; and upscaling of temporally sparse volume sequences, to generate refined temporal features. In this talk, I aim at providing a summary of the basic concepts underlying existing learning-based V2V and upscaling approaches, and a discussion of possible use cases for in situ volume visualization. Firstly, I will discuss the basic foundation of learning-based V2V and upscaling, and then shed light on the specific adaptations and extensions that have been proposed in visualization to realize such tasks. Next, I will discuss how these approaches can be employed for in situ visualization, and provide an outlook on future developments in the field.

    Speaker Bio: Rüdiger Westermann, born in Mai 1966, is a Professor for Computer Science at the Technical University Munich. He is head of the Chair for Computer Graphics and Visualization. He received his Diploma in Computer Science from the Technical University Darmstadt in 1991 and his Doctoral degree "with highest honours" from the University of Dortmund in 1996. From 1992 to 1997 he was a member of the research staff at the German National Institute for Mathematics and Computer Science in St. Augustin, Bonn, where he worked together with Wolfgang Krüger on parallel graphics algorithms. In 1998, he joined the Computer Graphics Group at the University of Erlangen-Nuremberg as a research scientist. Before he became an Assistant Professor in the Visualization Group at the University of Stuttgart in 1999 he was a Research Assistant in the Mulitres Group at Caltech and a Visiting Professor with the Scientific Computing Laboratory at the University of Utah. In 2001 he was appointed by the RWTH-Aachen as an Associate Professor for Scientific Visualization in the Department of Computer Science. Since 2003, Rüdiger Westermann is Chair of the Computer Graphics and Visualization group. In 2012, he was honored an ERC Advanced Grant worth 2.3 million Euros for research in the area of uncertainty visualization. Since 2015, he is part of the Transregional Collaborative Research Center “Waves to Weather”, where he supports meteorologists with visual analytics and deep learning approaches for identifying the limits of weather predictability. His recent research activities include stress-guided topology optimization with Prof. Jun Wu from TU Delft, as well as learning-based methods for data visualization and reconstruction, compression and feature analysis.

    Live Stream: http://live.bilibili.com/24003948

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    Session Chair: Wei Chen

    Zhejiang University

    Session Chair Bio: Wei Chen is a professor in State Key Lab of CAD&CG at Zhejiang University, P. R. China. His current research interests include visualization, visual analytics and bio-medical image computing. He has published more than 70 IEEE/ACM Transactions and IEEE VIS papers. His Chinese books on visualization are the unique books on visualization in China. He actively served in many leading conferences and journals, like IEEE PacificVIS steering committee, ChinaVIS steering committee, paper co-chairs of IEEE VIS, IEEE PacificVIS, IEEE LDAV and ACM SIGGRAPH Asia VisSym. He is an associate editor of IEEE TVCG, IEEE TBG, ACM TIST, IEEE CG&A, FCS, Data Intelligence and JOV.







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    Webpage: http://chinavis.org/lectures/english/index_en.html
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    About CSIG-VIS

    The China Society of Image and Graphics, Technical Committee on Visualization and Visual Analytics (CSIG-VIS) is the first technical committee on visualization and visual analytics in China. The technical committee aims to develop a communication platform for stakeholders in academia and industry, to discuss the trends and opportunities in the era of big data, to promote the discipline development and talent cultivation, to push forward the research and applications in the related disciplines, and ultimately to build a sustainable ecosystem involving industry, universities, and other research institutes. The technical committee, officially established on December 23, 2017, already attracts more than 100 members from various affiliations, including domestic and international universities and companies.

    About The CSIG-VIS International Lecture Series

    The CSIG-VIS International Lecture Series, launched by the China Society of Image and Graphics, Technical Committee on Visualization and Visual Analytics, invites renowned experts to share their visions of the research trends and latest progress in visualization. These biweekly lectures are conducted in Thursday, and please refer to http://chinavis.org /lectures/english/index_en.html for details.