My name is Zhutian Chen (陈竹天), currently a Ph.D. candidate at Hong Kong University of Science and Technology. I’m a member of HKUST VisLab, supervised by Prof. Qu Huamin. I received my bachelor degree from South China University of Technology in 2015, where I worked in CIKE group as an undergraduate research assistant advised by Prof. Yi Cai.
My research interests are in Information Visualization, Augmented Reality, and Machine Learning. Specifically, I have been working on tools and techniques powered by deep learning to facilitate the creation of data-driven infographics in and for AR environments. I characterize my research as Futuristic Infographics Creation.
I am available on the job market.
Prefer research position (e.g., postdoc and researcher) at any base (i.e., worldwide!)
Find my [ CV ] and contact me at: firstname.lastname@example.org
Towards Automated Infographic Design: Deep Learning-based Auto-Extraction of Extensible Timeline In print
IEEE Transactions on Visualization and Computer Graphics (InfoVis), 2019
LassoNet: Deep Lasso-Selection of 3D Point Clouds In print
IEEE Transactions on Visualization and Computer Graphics (SciVis), 2019
MARVisT: Authoring Glyph-based Visualization in Mobile Augmented Reality
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2018
Exploring the Design Space of Immersive Urban Analytics
Visual Informatics, 2017
StreamExplorer: A Multi-Stage System for Visually Exploring Events in Social Streams
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2017
Immersive Urban Analytics through Exploded Views
Workshop Proceedings of IEEE VIS 2017: Immersive Analytics
Animated Narrative Visualization for Video Clickstream Data
Proceedings of ACM SIGGRAPH ASIA Visualization Symposium, 2016
Blossom: Design of a Tangible Interface for Improving Intergenerational Communication for the Elderly
Proceedings of ACM Interactive Technology and Ageing Populations (ITAP), 2016
STAC: Enhancing Stacked Graphs for Time Series Analysis
Proceedings of IEEE Pacific Visualization Symposium (PacificVis), 2016