时间：2017年8月19日星期六
地点：浙江大学紫金港校区蒙民伟楼CAD&CG国家重点实验室402室

Morning:
9:00 – 9:40 Opening & Keynote by Leila
Topology-based Methods for spatial data analysis and visualization

9:40 – 10:40 Panel: How to increase the visibility of young Chinese researchers?

10:40 – 11:00 Tea Break.

11:00-12:15 Graphics&VIS Talks:
Ligang Liu:Smooth Assembled Mappings for Large-Scale Real Walking in VR
Lei Shi: Blockwise Human Brain Network Visual Comparison Using NodeTrix Representation
Yingcai Wu: Spatio-temporal Data Visualization
Bin Wang: Gauss Surface Reconstruction
Liang Wan: Panoramic Image Processing

Afternoon:
2:00 – 2:40 Keynote by Hanan
Reading News with Maps by Exploiting Spatial Synonyms

2:40 – 3:40 VIS&Graphics Talks:
Shixia Liu: Interpretable Machine Learning with Interactive Visualization
Yunhai Wang: Task-driven Automated Data Visualization
Jin Huang: Hex Remeshing
Dongming Yan: Isotropic Surface Remeshing without Large and Small Angle

3:40 – 4:00 Tea Break.

4:00-5:00 Demo Session

Leila De Floriani
University of Maryland at College Park

Keynote title: Topology-based Methods for spatial data analysis and visualization

Abstract:
Analyzing large spatial data sets requires efficient data management techniques, powerful analysis algorithms and visualization methods which allow domain experts to effectively interact with data. Advanced tools from combinatorial topology, such as persistent homology and Morse theory, provide a theoretically well-justified, and parameter-free way to extract the complex intrinsic structures of data in a very concise format, but are computationally intensive for current large-size data sets. In this talk I will present our work in topological analysis of big spatial data, specifically point data equipped with one or more function values: scalar fields (terrains, 2D or 3D images, unstructured volume data sets, etc.), and multifields, which are collections of fields with different modalities (e.g., pressure and density in physical simulations). I will focus on topology-based visual analytics tools to support interactive data analysis, and discuss scalability issues.

Biography:
Leila De Floriani is a Professor at the University of Maryland at College Park. She has been Professor of Computer Science at the University of Genova in Italy since 1990, where she founded the Geometry and Computer Graphics group, and where she has been the Director of the PhD Program in Computer Science for eight years. She has also held positions at the Italian National Research Council, at the University of Nebraska, at Rensselaer Polytechnic Institute, and at the University of Maryland.

Leila De Floriani has written over 280 publications in the fields of geometric and solid modeling, shape analysis, scientific data visualization, terrain modeling and geospatial data processing, which have appeared in major international journals and conferences. The main focus of her current research is in topological data analysis, geometric and topological data representations, geometric algorithms for scientific visualization and topology-based visual analytics.

Leila De Floriani is the Editor-in-Chief of the IEEE Transactions on Visualization and Computer Graphics. She is currently an Associate Editor of Graphical Models and of the ACM Transactions on Spatial Algorithms and Systems, and of GeoInformatica. She served on more then 150 program committees of the major international conferences in geometric modeling, computer graphics, visualization, and geospatial data processing. She is a Fellow of the IEEE, a Fellow of the International Association for Pattern Recognition (IAPR), a Member of the ACM and of the Eurographics Association. She is serving as a Member of the IEEE Computer Society Board of Governors for the years 2017-2019.

Hanan Samet
University of Maryland at College Park

Keynote title: Reading News with Maps by Exploiting Spatial Synonyms

Abstract:
NewsStand is an example application of a general framework to enable people to search for information using a map query interface, where the information results from monitoring the output of over 10,000 RSS news sources and  is available for retrieval within minutes of publication.  The advantage of doing so is that a map, coupled with an ability to vary the zoom level at which it is viewed, provides an inherent granularity to the search process that facilitates an approximate search. This distinguishes it from today's prevalent keyword-based conventional search methods that provide a very limited facility for approximate searches and which are realized primarily by permitting a match via use of a subset of the keywords.  However, it is often the case that users do not have a firm grasp of which keyword to use, and thus would welcome the search to also take synonyms into account.  For queries to spatially-referenced data, the map query interface is a step in this direction as the act of pointing at a location (e.g., by the appropriate positioning of a pointing device) and making the interpretation of the precision of this positioning specification dependent on the zoom level is equivalent to permitting the use of spatial synonyms (i.e., letting spatial proximity play a role rather than only seeking an exact match of a query string).  Of course, this is all predicated on the use of a textual specification of locations rather than a geometric one, which means that one must deal with the potential for ambiguity. 

The issues that arise in the design of a system like NewsStand, including the identification of words that correspond to geographic  locations, are discussed, and examples are provided of its utility. More details can be found in the video at http://vimeo.com/106352925 which accompanies the ``cover article'' of the October 2014 issue of the  Communications of the ACM about NewsStand at http://tinyurl.com/newsstand-cacm
or a cached version at http://www.cs.umd.edu/~hjs/pubs/cacm-newsstand.pdf.

Biography:
Hanan Samet (http://www.cs.umd.edu/~hjs/) is a Distinguished University Professor of Computer Science at the University of Maryland, College Park and is a member of the Institute for Computer Studies.  He is also a member of the Computer Vision Laboratory at the Center for Automation Research where he leads a number of research projects on the use of hierarchical  data structures for database applications, geographic information systems, computer graphics, computer vision, image processing, games, robotics, and search.  He received the B.S. degree in engineering from UCLA, and the M.S. Degree in operations research and the M.S. and Ph.D. degrees in computer science from Stanford University. His doctoral dissertation dealt with proving the correctness of translations of LISP programs which was the first work in translation validation and the related concept of proof-carrying code.  He is the author of the recent book "Foundations of Multidimensional and Metric Data Structures" (http://www.cs.umd.edu/~hjs/multidimensional-book-flyer.pdf) published by Morgan-Kaufmann, an imprint of Elsevier, in 2006, an award winner in the 2006 best book in Computer and Information Science competition of the Professional and Scholarly Publishers (PSP) Group of the American Publishers Association (AAP), and of the first two books on spatial data structures "Design and Analysis of Spatial Data Structures", and "Applications of Spatial Data Structures: Computer Graphics, Image Processing, and GIS", both published by Addison-Wesley in 1990.  He is the Founding Editor-In-Chief of the ACM Transactions on Spatial Algorithms and Systems (TSAS), the founding chair of ACM SIGSPATIAL, a recipient of a Science Foundation of Ireland (SFI) Walton Visitor Award at the Centre for Geocomputation at the National University of Ireland at Maynooth (NUIM), 2009 UCGIS Research Award, 2010 CMPS Board of Visitors Award at the University of Maryland,  2011 ACM Paris Kanellakis  Theory and Practice Award, 2014 IEEE Computer Society Wallace McDowell Award, and a Fellow of the ACM, IEEE, AAAS, IAPR (International Association for Pattern Recognition), and UCGIS (University Consortium for Geographic Science).  He received best paper awards in the 2007 Computers & Graphics Journal, the 2008 ACM SIGMOD and SIGSPATIAL ACMGIS Conferences, the 2012 SIGSPATIAL MobiGIS Workshop, and the 2013 SIGSPATIAL GIR Workshop, as well as a best demo paper award at the 2011 and 2016 SIGSPATIAL ACMGIS Conferences.  His paper at the 2009 IEEE International Conference on Data Engineering (ICDE) was selected as one of the best papers for publication in the IEEE Transactions on Knowledge and Data Engineering.  He was elected to the ACM Council as the Capitol Region Representative for the term 1989-1991, and was an ACM Distinguished Speaker for the term 2008-2015.