Dr. Remco Chang (Tufts University, USA)

http://www.cs.tufts.edu/~remco/

Modern visualization systems often assume that the data can fit within the computer’s memory. With such an assumption, visualizations can quickly slice and dice the data and help the users examine and explore the data in a wide variety of ways. However, in the age of Big Data, the assumption that data can fit within memory no longer applies. One critical challenge in designing visual analytics systems today is therefore to allow the users to explore large and remote datasets at an interactive rate. In this talk, I will present our research in approaching this problem in a user-centric manner. In the first half of the talk, I will present preliminary work with the database group at MIT on developing a big data visualization system based on the idea of predictive prefetching and precomputation. In the second half of the talk, I will present mechanisms and approaches for performing prefetching that are based on user’s past interaction histories and their perceptual abilities.

Bio: Remco Chang is an Assistant Professor in the Computer Science Department at Tufts University. He received his BS from Johns Hopkins University in 1997 in Computer Science and Economics, MSc from Brown University in 2000, and PhD in computer science from the University of North Carolina at Charlotte in 2009. Prior to his PhD, 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, and human-computer interactions. His research has been funded by NSF, DHS, MIT Lincoln Lab, and Draper. He has had best paper, best poster, and honorable mention awards at InfoVis, VAST, CHI, and VDA. He is currently an associated editor of the ACM Transactions on Interactive Intelligent Systems (TiiS) and the Human Computation journals, and he has been a PC and in organizational roles in leading conferences such as InfoVis, VAST, and CHI. He received the NSF CAREER Award in 2015.