• Sep 1, 2017 - Pinned
    We are looking for strongly-motivated PostDoc, PhD, Master, and undergraduate students to join us! If you are interested in visualization research, please contact us.
  • Feb 5th, 2018
    Our paper A Semantic-based Method for Visualizing Large Image Collections has been accepted by IEEE TVCG.
  • Jan 17, 2018
    Media coverage of our recent work HomeFinder Revisited: see more details.
ZJUVIS founded in 2015 is a vi­su­al­iza­tion group in Zhe­jiang Uni­ver­sity, P.R. China. Our re­search aims to create novel in­for­ma­tion vi­su­al­ization, vis­ual an­a­lyt­ics, aug­mented/vir­tual re­al­ity, and hu­man com­puter in­ter­ac­tion tech­nol­ogy to em­power users to do an­a­lyt­i­cal rea­son­ing with big data in var­i­ous set­tings, such as ur­ban in­for­mat­ics, sports an­a­lyt­ics, be­hav­ior an­a­lyt­ics, and so­cial me­dia an­a­lyt­ics.

ImageVis TVCG 2018

Interactive visualization of large image collections is important and useful. We propose a novel co-embedding model to project images and the associated semantic keywords to the same 2D space. Our system naturally supports multi-scale visualization, navigation, and iterative refinements of the co-embedding layout.

Paper Video


Finding an ideal home is a difficult and laborious process. By characterizing user requirements and analytical tasks in the context of finding ideal homes, we designed ReACH, a novel visual analytics system that assists people in finding, evaluating, and choosing a home based on multiple criteria, including reachability.

Paper Video

iTTVis InfoVis 2017

We propose iTTVis, a novel interactive table tennis visualization system, which to our knowledge, is the first visual analysis system for analyzing and exploring table tennis data. iTTVis provides a holistic visualization of an entire match from three main perspectives, namely, time-oriented, statistical, and tactical analyses.

Paper Video Demo