Center for Health Data Visualization and Visual Analytics Research
About Center
Thake the advantages of Peking University's comprehensive and high-quality medical resources and international leading visual and visual analysis research foundation, the Health Data Visualization will focus on the analysis and application of medical health data, and pay attention to the common, major diseases and comprehensive medical information needs in China. We will provide advanced visualization software, hardware platforms and services to support critical data-driven decision-making, analysis and dissemination.
Our Research
Our center conducts visualization and visual analysis in the field of medical big data:
1. Task-oriented visualization and visual analysis technology and system: research and development of key technologies such as multi-scale spatiotemporal visual analysis, high-dimensional data visual analysis, and immersive data visual analysis environment technology for medical big data, development of corresponding visualization and visual analysis systems.
2. Decision-oriented visualization and visual analysis capabilities and platforms: Develop a variety of narrative-based visualizations for spatiotemporal-related tasks and support immersive platform interaction decisions.
3. Public-oriented visualization and visual analysis tools and services: Develop data visualization tools which are suitable for up-to-date media communication needs for medical big data information dissemination and popularization of science, and provide efficient and convenient visualization services.
Work basis
The core team has carried out long-term research on visualization and visual analysis. It has a good accumulation, and has established a visual laboratory with great international influence.
The core team has carried out extensive research work on high-dimensional data, social media and spatiotemporal data. The team carried out serialized visualization and visual analysis research work on social media represented by Weibo, and formed a series of visualization methods and tools including microblog events, microblog theme maps, microblog event maps, and microblog group user behavior spatiotemporal feature analytics system.
The core team has dozens of workstations and corresponding network environments with high-performance graphics acceleration hardware, as well as four 4-CPU high-performance computing nodes and dual 2-CPU compute node compute clusters for high-performance GPUs. Developed with a number of high-performance visual display and computing environments, it can provide an ultra-high resolution display environment of up to 130 million (2048X6400) pixels, providing the experimental environment required for visual analysis.
The core team has won many awards in the international visual analysis data competition in recent years.
Leadership and Management
Xiaoru Yuan is a tenured faculty member in the School of Electronics Engineering and Computer Science. He received Bachelor degrees in chemistry and law from Peking University, China, in 1997 and 1998, respectively. He received the Ph.D. degree in computer science in 2006, from the University of Minnesota at Twin Cities. His primary research interests are in the field of scientific visualization, information visualization and visual analytics. He has co-authored over 60 technical papers in IEEE Visualization, IEEE Information Visualization, IEEE TVCG, IEEE EuroVis, IEEE PacificVis and other major international visualization conference and journals. His co-authored work on high dynamic range volume visualization received Best Application Paper Award at the IEEE Visualization 2005 conference. He and his student team won awards over 7 times in IEEE VAST Challenges. He served on the program committees of IEEE VIS, EuroVis, and IEEE PacificVis. He was organization co-chair of IEEE PacificVis 2009, program chair of VINCI 2010, and poster chair of IEEE VIS 2015/2016 and paper chair of IEEE VIS 2017and PacificVis 2015. He founded ChinaVis conference in 2014. He also serves on the editorial board of CCF journal of CAD&CG，Springer Journal of Visualization, and as guest editor of IEEE TVCG and IEEE CG&A. see http://vis.pku.edu.cn/wiki
