Xiaoxuan Mao
- (2025): A novel approach combining indoor mobile measurements and interpretable machine learning to unveil highly-resolved indoor air pollution. In: Building and Environment, v. 270 (February 2025).
- (2024): A hybrid spatiotemporal model combining graph attention network and gated recurrent unit for regional composite air pollution prediction and collaborative control. In: Sustainable Cities and Society, v. 116 (December 2024).
- (2024): Enhancing urban real-time PM2.5 monitoring in street canyons by machine learning and computer vision technology. In: Sustainable Cities and Society, v. 100 (January 2024).
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