Minwei Zhao
Biographic Data
| ID | 8833232 |
|---|---|
| NAME | Minwei Zhao |
| GIVEN NAMES | Minwei |
| FAMILY NAME | Zhao |
| SIGNATURE | ZHAO M |
| AFFILIATIONS | Hong Kong University of Science and Technology |
| ORCID | 0000-0002-6380-5426 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Ust-GNN
Understanding how social, demographic, environmental, and spatial factors jointly shape urban outcomes is essential for sustainable urban development and evidence-based policy. Traditional statistical approaches often struggle to capture complex non-linear relationships, while many machine learning methods overlook the joint roles of spatial autocorrelation and network topology in urban systems. Recent advances in GeoAI have addressed these chall…
Theory-informed and interpretable graph learning for urban commuting flows
Beyond single snapshots
Perceiving the fine-scale urban poverty using street view images through a vision-language model
Measuring urban nighttime vitality and its relationship with urban spatial structure
Nighttime vitality has garnered attention in recent years as an important indicator reflecting urban economy and quality of life. However, it is difficult to characterize this intangible issue. As a response, this study employed a data-driven approach to measure nighttime vitality and explored its relationships with urban spatial structure. Specifically, the data from Meituan.com—the largest Chinese shopping platform for local consumer products a…
No prominent works on this page.
Measuring urban nighttime vitality and its relationship with urban spatial structure
Nighttime vitality has garnered attention in recent years as an important indicator reflecting urban economy and quality of life. However, it is difficult to characterize this intangible issue. As a response, this study employed a data-driven approach to measure nighttime vitality and explored its relationships with urban spatial structure. Specifically, the data from Meituan.com—the largest Chinese shopping platform for local consumer products a…
Perceiving the fine-scale urban poverty using street view images through a vision-language model
Ust-GNN
Understanding how social, demographic, environmental, and spatial factors jointly shape urban outcomes is essential for sustainable urban development and evidence-based policy. Traditional statistical approaches often struggle to capture complex non-linear relationships, while many machine learning methods overlook the joint roles of spatial autocorrelation and network topology in urban systems. Recent advances in GeoAI have addressed these chall…
Theory-informed and interpretable graph learning for urban commuting flows
Beyond single snapshots
Urban Transport and Accessibility (3 works) · Computer Science (2 works) · Geography (2 works) · Graph (2 works) · Human Mobility and Location-Based Analysis (2 works) · Impact of Light on Environment and Health (2 works) · Urban Green Space and Health (2 works) · Advanced Graph Neural Networks (1 work) · Artificial Intelligence (1 work) · Artificial neural network (1 work)