Two recent trends have brought opportunities and challenges in data visualization research. First, data are increasing in size and complexity across problem domains, demanding interpretable and performant visualization systems. In addition, more diverse users, such as scientists, analysts, journalists, and designers, need to work with data as an integral part of their jobs. They require visualization tools that offer low barriers of entry without sacrificing analytic or expressive power.
I will present research projects that address these two challenges from a human-centered perspective. To support exploratory analysis of large multivariate and event sequence datasets, I use perceptual and interactive scalability as the driving principle to propose new interaction techniques. To make visualization tools accessible to a broader range of users, novel visualization process models can power the design and construction of natural language interfaces and visualization authoring systems. These techniques and models lay the foundation for future research on enabling a fluid exchange of tools, designs and critiques in a visualization ecosystem.
Zhicheng "Leo" Liu a research scientist at the Creative Intelligence Lab, Adobe Research, where he works on data visualization and human-computer interaction. Before joining Adobe, he was a postdoctoral fellow at the Department of Computer Science of Stanford University. He completed a PhD in the Human-Centered Computing program at Georgia Tech. His research has received two Best Paper Awards at ACM CHI, a Test of Time Award at IEEE VAST, multiple Best Paper Honorable Mentions at IEEE InfoVis, IEEE VAST and ACM CHI, and dissertation awards from Georgia Tech and IEEE Visualization and Graphics Technical Committee. The visualization tools developed by him and collaborators are adopted by users around the world.