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Background
Research vision is to develop AI-based solutions to address real-world challenges in social computing, urban computing, and environmental science.
AI + Social Computing: Focuses on online information diffusion prediction and credibility assessment (e.g., rumor/fake news detection); recently interested in predictability of economic behaviors (e.g., stock prediction).
AI + Urban Computing: Applies AI to urban development, including traffic (vehicle and metro) flow prediction, human mobility analysis from online check-in data, and urban region modeling via geographic interactions among entities (e.g., shopping centers, restaurants).
AI + Environmental Science: Interdisciplinary research integrating AI, environmental science, and physics, with a focus on water management.
Experienced in extracting meaningful features from multi-modal data (text, images, dynamic networks, videos, time-series) for real-world downstream tasks.