1. 国家自然科学基金优秀青年科学基金项目(海外),水资源系统分析与模拟,主持
2. 国家自然科学基金委面上项目,气候变化下流域多部门用水行为动态响应模拟与适应性调控,2027-2030,主持
3. 国家自然科学基金委青年项目,缓解城市内涝风险目标下的绿色屋顶精准推广政策研究,2023-2025,主持
4. 京津冀环境综合治理国家科技重大专项“京津冀典型生态空间环境增容与稳定性提升关键技术及应用”子课题,生态-环境-资源耦合的生态空间承载力阈值确定,2026-2029,主持
5. 国家重点研发计划“珠江流域关键生源要素多介质溯源与协同管控”子课题,东江流域水体氮污染调控要素与响应规律,2022-2026,主持
6. 国家重点研发计划“粤港澳大湾区复合生态系统减污降碳协同调控技术”子课题,城市群固碳-减污与韧性提升的生态修复方案,2022-2026,主持
7. 广东省自然科学基金-面上项目,气候变化下兼顾减污降碳防洪的城市绿色基础设施空间布局优化研究,2024-2026,主持
8. 广东省自然科学基金-面上项目,多源数据融合下东江流域总氮浓度模拟与管控措施优化研究,2026-2028,主持
9. 中国工程院战略研究咨询项目,区域河湖格局演变与“幸福河湖”建设对策,参与
10.美国能源部,Center for Advanced Bioenergy and Bioproducts Innovation (DE-SC0018420),2018-2022,参与
目前已在国际主流SCI期刊发表学术论文三十余篇,其中第一/通讯作者SCI论文二十余篇,发表于Water Resources Research,Environmental Science & Technology,Renewable & Sustainable Energy Reviews等水资源/水环境领域顶级期刊。已授权专利十余项。部分代表性成果如下:
Yang, P. and Cai, X.* (2026). Filling the cellulosic bio-economy gap by utilizing a wedge approach combined with stakeholder collaboration. Renewable Energy, 262, 125419.
Zhou, S.†, Yang, P.†, Gan, Y., & Tan, Q.* (2026). A Hybrid Bayesian data fusion framework to enhance watershed nitrogen modeling by integrating in situ observations with spatial inversion data. Water Resources Research, 62(4), e2025WR041979; †共同一作.
Yi, K., Yang, P.*, Yang, S., Bao, S., Xu, Z., & Tan, Q. (2025). On the accuracy requirement of surrogate models for adequate global sensitivity analysis of urban low-impact development model. Journal of Hydrology, 657, 133102.
Yang, P., Cai, X.*, Hu, X., Zhao, Q., Lee, Y., Khanna, M., ... Iutzi, F. (2022). An agent-based modeling tool supporting bioenergy and bio-product community communication regarding cellulosic bioeconomy development. Renewable and Sustainable Energy Reviews, 167, 112745.
Yang, P.†, Piao, X.†, Cai, X.* (2022). Water Requirement for Biorefinery to Meet the Renewable Fuel Standard in the Contagious United States. Environmental Science & Technology, 56(6), 3748–3757; †共同一作.
Niu, G.,Yang, P.*, Zheng, Y.*, Cai, X., & Qin, H. (2021). Automatic quality control of crowdsourced rainfall data with multiple noises: A machine learning approach. Water Resources Research, 57(11), e2020WR029121.
Yang, P., Zhao, Q., and Cai, X.* (2020). Machine Learning Based Estimation of Land Productivity in the Contiguous US Using Biophysical Predictors. Environmental Research Letters, 15(7): 074013.
Yang, P., Ng, T. L.*, and Cai, X.* (2019). Reward-based Participant Management for Crowd-Sourcing Rainfall Monitoring: An Agent-Based Model Simulation. Water Resources Research, 55(10): 8122-41.
Yang, P. and Ng, T. L.* (2019). Fast Bayesian Regression Kriging Method for Real‐Time Merging of Radar, Rain Gauge, and Crowdsourced Rainfall Data. Water Resources Research, 55(4): 3194-3214.
Yang, P. and Ng, T. L.* (2017). Gauging through the Crowd: A Crowd-Sourcing Approach to Urban Rainfall Measurement and Stormwater Modeling Implications. Water Resources Research, 53(11): 9462-9478.