Zhicheng "Leo" Liu - Human-Machine Symbiosis in Visual Analytics and Visualization Design
Speaker
Zhicheng "Leo" Liu
University of Maryland, College Park
Host
Arvind Satyanarayan
CSAIL MIT
Abstract:
A tight coupling of humans and machines is often required to address many challenges in data visualization research. In this talk, I will present two threads of work that explore different configurations of human-machine symbiosis to effectively support analytic and design tasks. The first thread focuses on interactive analysis of event sequence data, where the machine automatically generates visual summaries of the data, and the user employs the visual summaries as overviews to guide analysis. The second thread focuses on visualization authoring and reuse through manipulable semantic components, where the user specifies desired designs, and the machine assists by performing data binding and example deconstruction. Based on these two threads, I will discuss research opportunities going forward to enhance human-machine symbiosis in data visualization.
Bio:
Zhicheng "Leo" Liu is an assistant professor in the department of computer science at the University of Maryland College Park. He directs the Human-Data Interaction research group, focusing on human-centered techniques and systems that support interactive data analysis and visual communication. Before joining UMD, he worked at Adobe Research as a research scientist and at Stanford University as a postdoc fellow. He obtained his Ph.D. at Georgia Tech. His work has been recognized with a Test-of-Time award at IEEE VIS, and multiple Best Paper Awards and Honorable Mentions at ACM CHI and IEEE VIS.
The talk will also be streamed over Zoom: https://mit.zoom.us/j/97604964013.
A tight coupling of humans and machines is often required to address many challenges in data visualization research. In this talk, I will present two threads of work that explore different configurations of human-machine symbiosis to effectively support analytic and design tasks. The first thread focuses on interactive analysis of event sequence data, where the machine automatically generates visual summaries of the data, and the user employs the visual summaries as overviews to guide analysis. The second thread focuses on visualization authoring and reuse through manipulable semantic components, where the user specifies desired designs, and the machine assists by performing data binding and example deconstruction. Based on these two threads, I will discuss research opportunities going forward to enhance human-machine symbiosis in data visualization.
Bio:
Zhicheng "Leo" Liu is an assistant professor in the department of computer science at the University of Maryland College Park. He directs the Human-Data Interaction research group, focusing on human-centered techniques and systems that support interactive data analysis and visual communication. Before joining UMD, he worked at Adobe Research as a research scientist and at Stanford University as a postdoc fellow. He obtained his Ph.D. at Georgia Tech. His work has been recognized with a Test-of-Time award at IEEE VIS, and multiple Best Paper Awards and Honorable Mentions at ACM CHI and IEEE VIS.
The talk will also be streamed over Zoom: https://mit.zoom.us/j/97604964013.