Research Focuses
Artificial Intelligence
With fruitful datasets from urban realm, I work on integrating deep learning architectures (e.g., transformers, graph neural networks, diffusion models) to build predictive, generative, and decision-support systems. Keywords: Representation learning, Generative AI, Spatial-Temporal Analysis.
Urban Data Science
Urban Data Science explores how large-scale environmental, mobility, socioeconomic, and infrastructure datasets can be integrated to understand urban systems. I design scalable data pipelines that combine remote sensing, census microdata, mobility traces, sensor networks, and geospatial information to quantify spatial inequality, environmental exposure, and system resilience across cities. My work emphasizes reproducibility, multi-scale modeling, and policy-relevant insights.
Causal Inference
Understanding cause-and-effect relationships from observational data.
Complex Systems
Emergent behavior, network science, and dynamical systems modeling.