1. 2026.1-2029.12 国家自然科学基金青年项目（C类） 项目主持

2. 2025.7-2028.6 上海市自然科学基金青年项目  项目主持

3. 2025.4-2026.4  横向课题-低碳住宅立体绿化系统与居住品质提升技术  项目主持

4. 2025.8-2026.2  “创新设计与智能制造”学科群项目  项目主持

[1] Zhou, S., Geng, X., Zhao, J., Hei, J., Wu, T., Chen, Z., & Wu, Z. (2025). An LCZ-based machine learning framework for revealing spatial heterogeneity of thermal comfort in high-density areas: Enhancing explainability and fine-grid scale resolution. Sustainable Cities and Society, 106873.

[2] Zhou, M., Zhou, S*., Hei, J., Yang, S., Liu, Q., Yang, T., & Zhiqiang, W. (2025). Impact of innovation drivers in Chinese cities: Machine learning analysis using XGBoost. Cities, 167, 106347.

[3] Zhou, S., Geng, X., Jia, W., Xu, H., Xu, X., Chen, H., ... & Wu, Z. (2025). Towards climate-adaptive equality in coastal megacities: Assessing urban flooding risk disparities and nonlinear effect of multidimensional indicators through an interpretable LightGBM-SHAP framework. Sustainable Cities and Society, 106809.

[4] Zhou, S., Jia, W., Geng, X., Xu, H., Diao, H., Liu, Z., ... & Wu, Z. (2025). Quantifying the spatiotemporal dynamics of urban flooding susceptibility in the greater bay area under shared socio-economic pathways using the SD-PLUS-LightGBM framework. Resources, Conservation and Recycling, 223, 108534.

[5] Wang, M., Xiong, Z., Zhou, S*., Zhao, J., Sun, C., Wang, Y., ... & Tan, S. K. (2025). Integrating generative AI and climate modeling for urban heat island mitigation. Ecological Informatics, 103284.

[6] Zhou, S., Xu, X., Xu, H., Zhao, Z., Yuan, H., Wang, Y., ... & Wu, Z. (2025). From heat resilience to sustainable co-benefits: Adaptive urban morphology generation based on multimodal data fusion and a novel generative framework. Sustainable Cities and Society, 106452.

[7] Wu, T., Chen, Z., Zhou, S*., Huang, R., Xing, P., Li, S., ... & Wu, Z. (2025). Joint evaluation of urban built environment's driving patterns on urban heat island (UHI) and urban moisture island (UMI). Sustainable Cities and Society, 106450.

[8] Xu, X., Zhou, S*., Xu, H., & Wu, Z. (2025). Advancing urban hub planning: A bibliometric analysis of concepts, effects evaluation, and spatial design. Land use policy, 152, 107507.

[9] Zhou, S., Jia, W., Diao, H., Geng, X., Wu, Y., Wang, M., ... & Wu, Z. (2025). A CycleGAN-Pix2pix framework for multi-objective 3D urban morphology optimization: enhancing thermal performance in high-density areas. Sustainable Cities and Society, 106400.

[10] Zhou, S., Diao, H., Wang, J., Jia, W., Xu, H., Xu, X., Wang, M., Sun, C., Qiao, R. and Wu, Z. Multi-stage optimization framework for synergetic grey-green infrastructure in response to long-term climate variability based on shared socio-economic pathways [J]. Water Research, 2025, 274, p.123091.ESI热点论文

[11] Zhou, S., Jia, W., Wang, M., Liu, Z., Wang, Y. and Wu, Z. Synergistic assessment of multi-scenario urban waterlogging through data-driven decoupling analysis in high-density urban areas: A case study in Shenzhen, China [J]. Journal of Environmental Management, 2024, 369, p.122330. 

[12] Zhou, S., Zhang, D., Wang, M., Liu, Z., Gan, W., Zhao, Z., Xue, S., Müller, B., Zhou, M., Ni, X. and Wu, Z*. Risk-driven composition decoupling analysis for urban flooding prediction in high-density urban areas using Bayesian-Optimized LightGBM [J]. Journal of Cleaner Production, 2024, 457, p.142286. ESI高被引论文

[13] Zhou, S., Diao, H., Wang, M., Jia, W., Wang, Y., Liu, Z., Gan, W., Zhou, M., Wu, Z. and Zhao, Z. Knowledge mapping and emerging trends of urban resilient infrastructure research in urban studies: Precedent work, current progress and future perspectives [J]. Journal of Cleaner Production, 2024, 452, p.142087. 

[14] Zhou, S., Wang, Y., Jia, W., Wang, M., Wu, Y., Qiao, R. and Wu, Z*. Automatic responsive-generation of 3D urban morphology coupled with local climate zones using generative adversarial network [J]. Building and Environment, 2023, 245, p.110855.

[15] Zhou, S., Liu, Z., Wang, M., Gan, W., Zhao, Z. and Wu, Z*. Impacts of building configurations on urban stormwater management at a block scale using XGBoost [J]. Sustainable Cities and Society, 2022, 87, p.104235.

[16] 周士奇,贾蔚怡,刘治宇,&王墨.建成环境视角下高密度城市内涝风险预测与影响因素机器学习解析:以深圳市为例[J].景观设计学(中英文), 2024, 12(5):48-67.

[17] Qiao, R., Gao, S., Liu, X., Xia, L., Zhang, G., Meng, X., Liu, Z., Wang, M*., Zhou, S*. and Wu, Z*. Understanding the global subnational migration patterns driven by hydrological intrusion exposure [J]. Nature Communications, 2024, 15(1), p.6285. 

[18] Wang, M., Fan, H., Yuan, H*., Zhang, D., Su, J., Zhou, S*., Zhang, Q. and Li, J. Urban flooding damage prediction in matrix scenarios of extreme rainfall using a convolutional neural network [J]. Journal of Hydrology, 2024, 644, p.132069. 

[19] Wang, M., Chen, B., Zhang, D*., Yuan, H., Rao, Q., Zhou, S*., Li, J., Wang, W. and Tan, S.K. Comparative life cycle assessment and life cycle cost analysis of centralized and decentralized urban drainage systems: A case study in Zhujiang New Town, Guangzhou, China [J]. Journal of Cleaner Production, 2023, 426, p.139173. 

[20] Wang, M., Li, Y., Yuan, H., Zhou, S*., Wang, Y*., Ikram, R.M.A. and Li, J. An XGBoost-SHAP approach to quantifying morphological impact on urban flooding susceptibility [J]. Ecological Indicators, 2023, 156, p.111137. ESI高被引论文