activity
20232026
most citedInterpreting core forms of urban morphology linked to urban functions with explainable graph neural network

11 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CY2026

Reconfiguring Geovisualization in the Age of Generative AI: Insights from Domain Experts

Mengyi Wei, Chenyu Zuo, Jiaying Xue +5

GenAI is increasingly integrated into geovisualization, yet its broader implications for professional practice are insufficiently understood. To examine these implications, we cond…

cs.CY2026

Inclusive Learning Analytics with Embedded Data Comics: A Conceptual Framework for Public Understanding of AI Ethics

Mengyi Wei, Chenyu Zuo, Dongsheng Chen +1

Public awareness of AI ethics plays a crucial role in fostering the responsible and sustainable development of AI technology. However, finding effective ways to promote public unde…

cs.CE2025★ 11 cited

Interpreting core forms of urban morphology linked to urban functions with explainable graph neural network

Dongsheng Chen, Yu Feng, Xun Li +3

Understanding the high-order relationship between urban form and function is essential for modeling the underlying mechanisms of sustainable urban systems. Nevertheless, it is chal…

cs.CY2024

Mapping AI Ethics Narratives: Evidence from Twitter Discourse Between 2015 and 2022

Mengyi Wei, Puzhen Zhang, Chuan Chen +3

Public participation is indispensable for an insightful understanding of the ethics issues raised by AI technologies. Twitter is selected in this paper to serve as an online public…

cs.DB2023★ 2 cited

Integrating 3D City Data through Knowledge Graphs

Linfang Ding, Guohui Xiao, Albulen Pano +6

CityGML is a widely adopted standard by the Open Geospatial Consortium (OGC) for representing and exchanging 3D city models. The representation of semantic and topological properti…