Javid Chien-Hsin Hsueh, received his Master degree in Computer Science at UC Davis under Prof. Kwan-Liu Ma in the VIDI (Visualization and Interface Design Innovation) research group. His research interests include information visualization, visual analytics, and user interface design.
Now Javid is a visualization engineer at Uber. He mostly works on graph visualization and self-service dashboarding tool for helping internal users to find business insights.More on LinkedIn
Chien-Hsin Hsueh, Jacqueline Chu, Kwan-Liu Ma
Ocean track is our exhibit prototype that encourages museum visitors to learn about marine animal behaviors through interactive data visualization. The goal is to have visitors draw comparisons between animal behaviors, similarly to how scientists would, to make insights and discoveries.
Chien-Hsin Hsueh, Tai Stillwater, Ken Kurani, Justin Woodjack, Kwan-Liu Ma
Driving behavior is the major factor to impact the energy usage between different drivers. In this project, we proposed a new visual metaphor for representing driving behavior of history trips. The fully interactive web-based system enables users to investigate the driving behavior according to different aspects.
Chien-Hsin Hsueh, Justin Woodjack, Tai Stillwater, Ken Kurani, Kwan-Liu Ma
Visualizing trajectory attribute data is challenging because it involves showing the trajectories in their spatial-temporal context as well as the attribute values associated with the individual points of trajectories. In this project, the goal is to build a system to visualize sets of trajectories and provide useful information to analysts to perform related tasks.
Yuzuru Tanahashi, Chien-Hsin Hsueh, Kwan-Liu Ma
Storyline visualization is a technique used to depict the temporal dynamics of social interactions. The visualization can convey both global trends and local interactions in the data. However, previous methods for automating storyline visualizations are overly slow, failing to achieve some aspects of realtime interactive visualization. Our layout algorithm is based on incremental greedy algorithm, allowing us to effectively deal with streaming data. We show that the resulting visualizations have significantly improved performance and readability compared to existing techniques.
Live in the future, then build what’s missing.
Javid Chien-Hsin Hsueh 薛健鑫
Visualization Engineer, Uber,