NTNU


Keynotes

Image

Remco Chang

Tufts University

Chair: Kwan-Liu Ma

Topic: A Visualization Is Worth a Thousand Queries: Towards a Foundation for Reasoning in Visual Analytics

Date: 9:30 ~ 10:30, April 23

Abstract: As visual analytics continues to mature, so too must our understanding of its conceptual foundations. In this talk, I propose a framing of visualization in terms of functions, spaces, and grammar, offering a perspective aimed at formalizing how visualizations mediate between data, analytic tasks, and reasoning. We begin with the notion of visualization as a function: a mapping from data and interaction parameters to visual representations. This functional view, illustrated through systems like NeuralCubes, positions visualizations as surrogates for query execution. More broadly, it invites us to consider query spaces: the range of potential questions a visualization can support, suggest, or help refine. At the heart of this framing is the concept of design-specific transformations, where visual encodings embed analytic computation directly into their form. A pie chart, for example, does more than display values; it pre-computes part-to-whole relationships, reducing cognitive effort and guiding interpretation. These often-invisible transformations shape the interpretive work a visualization performs and influence the kinds of questions it can help answer. Making them explicit allows us to more precisely describe a visualization’s analytic affordances. Building on this, we introduce a hypothesis grammar, a conceptual framework that captures the structure of analytic questions. This grammar makes it possible to represent ambiguous or underspecified queries as modifiable query spaces. By aligning user tasks with data transformations and visual encodings, it helps enumerate the space of testable questions a visual analytics system can meaningfully support. Together, these ideas suggest a path toward a more formal theory of visual analytics. By conceptualizing visualizations as functions, spaces, and grammars, we can bring data, task, and visual design into a unified framework—one that offers a more rigorous and operational foundation for the visual analytics community.

Bio: Remco Chang is a Professor in the Computer Science Department at Tufts University. He received his BA in Computer Science and Economics from Johns Hopkins University, his MSc from Brown University, and his PhD from the University of North Carolina at Charlotte. Before his PhD, he worked at Boeing on real-time flight tracking and visualization software and later served as a research scientist at UNC Charlotte. His research interests include visual analytics, information visualization, human-computer interaction (HCI), and databases, with support from the NSF, DARPA, Navy, DOD, Walmart Foundation, Merck, DHS, MIT Lincoln Lab, and Draper. He is a co-founder of two startups, Hopara.io and GraphPolaris, and has received best paper, best poster, and honorable mention awards at VIS, CHI, EuroVis, and VDA. He served as Paper Chair of IEEE VIS in 2018 and 2019 and was the General Chair for VIS 2024. He is an associate editor for ACM Transactions on Interactive Intelligent Systems (TiiS) and IEEE Transactions on Visualization and Computer Graphics (TVCG) and was awarded the NSF CAREER Award in 2015. His former PhD advisees and postdocs now hold faculty positions at institutions including Smith College (x2), DePaul University, Washington University in St. Louis, University of Washington, University of San Francisco, University of Colorado Boulder, WPI, San Francisco State, Utrecht University, and Brandeis, as well as research positions at organizations such as Google, Draper, Meta, MIT Lincoln Lab (x2), the National Renewable Energy Lab, and Idaho National Lab.

Image

Ross Maciejewski

Arizona State University

Chair: Remco Chang

Topic: Reflections on Visual Analytics, Past, Present and Future

Date: 11:00 ~ 12:00, April 25

Abstract: In 2004, Visual Analytics emerged as an outgrowth of scientific visualization and information visualization with a focus on the mechanisms of analytic reasoning facilitated by interactive visual interface, and over the past 20 years, researchers have explored the design space of visual analytics through various system and application developments. In this talk, I will discuss some of the early visual analytics applications and technology that are still relevant today, reflect on modern visual analytics systems designs, and identify research directions for visual analytics in this era of Artificial Intelligence as we continue working to detect the expected and discover the unexpected.

Bio: Ross Maciejewski is a Professor at Arizona State University and Director of the School of Computing and Augmented Intelligence. He serves as the co-Director of the Center for Accelerating Operational Efficiency - a Department of Homeland Security Center of Excellence. His primary research interests are in the areas of visualization and explainable AI. He has served on the organizing committees for the IEEE Conference on Visual Analytics Science and Technology, the IEEE/VGTC EuroVis Conference, and as the co-chair of the Visualization Executive Committee (VEC) (2021 - 2024). He is currently an Associate Editor in Chief for IEEE Transactions on Visualization and Computer Graphics. Professor Maciejewski is a recipient of an NSF CAREER Award (2014), and his work has been recognized through a variety of awards at the IEEE Visual Analytics Contest (2010, 2013, 2015), a best paper award in EuroVis 2017, and CHI Honorable Mention Awards (2018, 2022).



arrow-up icon