Big Data Visual Analytics: Challenges and Opportunities

Lecture / Panel
For NYU Community

Speaker: Remco Chang, Tufts University


Visual analytics is a fast growing discipline that combines visualization, interaction, and data analysis in solving large and complex problems that require human understanding and reasoning. In recent years, visual analytics tools have been widely adopted across a wide range of disciplines. However, one critical, and yet common challenge that has emerged is the issue of Big Data. Specifically, maintaining interactivity and fast rendering in a visual analytics system become increasingly difficult as the scale (number of rows) and complexity (number of dimensions) of the data increase.

In this talk, I will give an overview of the current state-of-the-art systems and research in the visual analytics community, and discuss some of the open challenges as well as opportunities.  In particular, I will focus on recent efforts by our research group at Tufts University in (1) using cognitive factors to identify a user's analytic profile that can lead to predictive prefetching; (2) understanding how a user can interact with high dimensional data in 2D, and (3) developing user-interface design guidelines that can impact the fetching performance of the back-end data storage system.


Remco Chang is an Assistant Professor in the Computer Science Department at Tufts University. He received his B.S from Johns Hopkins University in 1997 in Computer Science and Economics, his MSc from Brown University in 2000, and his Ph.D. in computer science from UNC Charlotte in 2009. Prior to his Ph.D., he worked for Boeing developing real-time flight tracking and visualization software, followed by a position at UNC Charlotte as a research scientist. His current research interests include visual analytics, information visualization, HCI, urban modeling, and computer graphics.