ビジュアルコンピューティングセミナー2018-06
下記の要領で，今年度第 6 回のセミナーを開催しますのでご参集ください．
日 時 ：平成 3１年 3 月 20 日（水）13:30-15:00
場 所： 慶應義塾大学 矢上キャンパス 14 棟（創想館）2 階
14-201 室（セミナールーム１）（https://www.st.keio.ac.jp/about/access.html）
題 目：Immersive Analytics of Big Data
講 師： Arie E. Kaufman
Distinguished Professor of Computer Science
Director of the Center of Visual Computing (CVC)
Chief Scientist of the Center of Excellence in Wireless and Information Technology (CEWIT)
Stony Brook University, Stony Brook, New York, USA

要 旨：Scientists, engineers and physicians are confronted with an immeasurable amountof data. Immersive visualization environments can provide them with a novel way ofinteracting and reasoning with large datasets, a form of big data immersive analytics. Theseenvironments allow a user to utilize the entirety of his/her visual bandwidth and field ofregard, effectively engulfing the user in the data while enabling interaction and analysis,
either computationally (e.g., machine learning) or visually (e.g., visual analytics). We
present two stationary environments in addition to mobile head mounted displays. The firstis a custom-built 5-wall stereo Cave environment, called the Immersive Cabin. Combinedwith a range of interaction and navigation tools, the Cabin can support numerous interactive
applications of immersive analytics of big data. Current visualization displays, such as theCabin, however, have not kept up with the explosive growth in data size and resolution,
which is approaching our visual acuity. To ameliorate this challenge, we have developed alife-like, realistic immersive environment for big data, appropriately called the Reality Deck.
It is a one-of-a kind pioneering 1.5-billion-pixel immersive display facility – a uniqueassembly of 416 high-res display panels, an 80-GPU cluster, 7 miles of cables, IR tracking
cameras, sound system, and human-computer interaction techniques. We further depict
methods related to these immersive environments, such as a conformal deformation
rendering method for the visualization of datasets on partially-immersive platforms, and theinfinite canvas method for displaying “infinitely long” data. Demonstrated applications ofimmersive analytics of big data include biomedicine (especially cancer detection),architectural design, urban planning, molecular modeling, reconnaissance and security,
visual simulation, weather and climate, and entertainment.
講師略歴：Arie Kaufman is a Distinguished Professor of the Computer Science Department,
Director of the Center of Visual Computing (CVC), Chief Scientist of the Center of Excellencein Wireless and Information Technology (CEWIT), and Site Director of the NSF Industry
University Cooperative Research Center (IUCRC) for Visual and Decision Informatics (CVDI)
at Stony Brook University. He served as Chairman of the Computer Science Department
1999-2017. He has conducted research for 40 years in visualization, computer graphics,
virtual-reality, medical imaging and their applications, has published more than 300 refereed
papers, books, and chapters, has delivered more than 20 invited keynote/plenary talks, hasbeen awarded/filed more than 100 world-wide patents (most of which have been licensed),
and has been a principal/co-principal investigator on more than 100 research grants. He isa Fellow of the National Academy of Inventors (NAI), Fellow of IEEE, Fellow of ACM,
member of the European Academy of Sciences, the recipient of the IEEE Visualization CareerAward (2005), and inductee of the LI Technology Hall of Fame (2013), as well as numerous
other awards. He was the founding Editor-in-Chief of the IEEE Transaction on Visualization
and Computer Graphics (TVCG), 1995-1998. He was also the co-founder/papers co-chair ofIEEE Visualization Conferences; Volume Graphics Workshops, Eurographics/SIGGRAPH
Graphics Hardware Workshops, and ACM Volume Visualization Symposia. He was thedirector and chair of IEEE CS Technical Committee on Visualization and Graphics. He
received PhD in Computer Science from the Ben-Gurion University, Israel.
For more information, please visit:

http://www.cs.stonybrook.edu/∼ari

照会先 ：藤代（情報工学科，fuji@ics.keio.ac.jp）