Design problems in engineering typically involve a large solution space and several potentially conflicting criteria. Selecting a compromise solution is often supported by optimization algorithms that compute hundreds of ...

Despite the significance of tracking human mobility dynamics in a large-scale earthquake evacuation for an effective first response and disaster relief, the general understanding of evacuation behaviors remains limited. ...

The ability to perceive patterns in parallel coordinates plots (PCPs) is heavily influenced by the ordering of the dimensions. While the community has proposed over 30 automatic ordering strategies, we still lack empirical ...

In order to ensure sustainability, fishing operations are governed by many rules and regulations that restrict the use of certain techniques and equipment, specify the species and size of fish that can be harvested, and ...

Training data plays an essential role in modern applications of machine learning. However, gathering labeled training data is time-consuming. Therefore, labeling is often outsourced to less experienced users, or completely ...

Schematic transit maps (often called "metro maps" in the literature) are important to produce comprehensible visualizations of complex public transit networks. In this work, we investigate the problem of automatically ...

We present DRLViz, a visual analytics interface to interpret the internal memory of an agent (e.g. a robot) trained using deep reinforcement learning. This memory is composed of large temporal vectors updated when the agent ...

In the visualization community, it is often assumed that visual data storytelling increases memorability and engagement, making it more effective at communicating information. However, many assumptions about the efficacy ...

This paper describes results from an observational, exploratory study of visual data exploration in a large, multi-view, flexible canvas environment. Participants were provided with a set of data exploration sub-tasks ...

Through a design study, we develop an approach to data exploration that utilizes elastic visualizations designed to support varying degrees of detail and abstraction. Examining the notions of scalability and elasticity in ...