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Next Generation Visualization Interfaces
Speaker: Prof. Kwan-Liu Ma Department of Computer Science University of California, Davis Title: "Next Generation Visualization Interfaces" Date: Monday, 10 October 2005 Time: 4:00pm - 5:00pm Venue: Lecture Theatre F (near lift nos. 25/26) HKUST Abstract: Visualization transforms large quantities of, possibly multiple dimensional, raw data into graphical representations that exploit the high-bandwidth channel of the human visual system, leveraging the brain's remarkable ability to detect patterns and draw inferences. It has become an indispensable tool for many scientists and engineers. The process of data visualization is inherently iterative. A good visualization comes from experimenting with visualization and rendering parameters to bring out the most relevant information in the data. This iterative process if not carefully designed can be tedious and costly. In addition to improved rendering software and hardware technologies, new interface technologies have been designed to ease this process and thus reduce the cost of data visualization. In this talk I will introduce two such technologies. The first interface design employs an intelligent system to assist in the process of interactive volume classification and visualization. The intelligent system makes possible the use of higher dimensional classifications for complex segmentation tasks. In particular, it allows the user to focus on the data content and features of interest, rather than conducting manual tuning of multidimensional classification and rendering parameters. The second interface design facilitates sharing and reuse of the various information about data exploration to leverage the knowledge and experience that scientists gain from visualizing their data. For types of data visualization where the cost of producing images is high, and the relationship between the rendering parameters and the image produced is less than obvious, a visual representation of the exploration process can make the process more efficient and effective. Such a visual representation can be used as an interface to the data analysis and visualization process to dramatically improve explorability and facilitate collaboration. ************************ Biography: Professor Ma received his PhD in computer science from the University of Utah in 1993. During 1993-1999, he was with ICASE/NASA LaRC as a research scientist. In 1999, he joined UC Davis. In the following year, Professor Ma received the Presidential Early Career Award for Scientists and Engineers (PECASE) for his work in parallel visualization. In 2001, he received the Schlumberger Foundation Technical Award for his work in large data visualization. Professor Ma's research spans the fields of visualization, computer graphics, and high performance computing. His goal is to advance the state of the art in data visualization technology. Professor Ma is a member of IDAV (Institute for Data Analysis and Visualization). Currently, he is leading research projects in parallel rendering, volume modeling and visualization, artistically inspired illustrations, visual interface designs, and information visualization. Three main efforts are NSF ITR time-varying data visualization, DOE SciDAC visualizing accelerator simulations, and NSF ITR network security visualization. He is the editor of the VisFiles Column of the ACM SIGGRAPH's Computer Graphics Quarterly.