• Associate professor
• Name (Simplified Chinese):阎洁如
• Name (Pinyin):yanjieru
• School/Department:实验中心
• Education Level:Postgraduate (Postdoctoral)
• Business Address:纬地楼S103
• Degree:Doctoral degree
• Status:Employed
• Alma Mater:德国斯图加特大学

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阎洁如，女，2018年12月博士毕业于德国斯图加特大学，获工学博士学位；2019年-2023年在同济大学从事博士后研究；2023年7月进入土木与水利工程学院，负责实验中心/水力学实验室的日常管理，并从事教学与科研工作。主要研究方向包括：极端降水的分析和预报，城市水文，高分辨率降水场的实时模拟，随机天气模型等；主持国家自然科学基金青年基金项目、省部级项目共2项，参与国家自然科学基金面上项目、德国研究基金会项目、产学研合作项目共6项；发表SCI论文9篇，英文专著1部。主持/参与项目[1] 国家自然科学基金青年基金项目：基于数值模拟和非线性融合技术对高分辨率降水场实时构建的研究，42001369，2021.01-2023.12，在研，主持[2] 中国博士后科学基金面上项目：基于数值模拟和非线性融合技术对高分辨率雨量场实时构建的研究，2020M671219，2020.09-2022.08，结题，主持[3] 国家重大水体专项独立课题：苏州市饮用水安全保障技术集成与综合应用示范，2017ZX07201001，3390.87万，2017.1-2020.12，结题，参与[4] 国家自然科学基金面上项目：城市雨水系统光滑粒子动力学模拟理论研究，51778452， 80万，2018.01-2021.12，结题，参与[5] 国家自然科学基金面上项目：城市排水管网运行状态微机电技术诊断理论与应用，51978493，61万，2020.1-2023.12，在研，参与[6] 国家自然科学基金面上项目：基于深度强化学习的供水管网人机决策融合实时优化调度，52270093 ，54万，2023.1-2026.12，在研，参与[7] 产学研合作课题：温州市鹿城区丰门街道排水管网运行状态诊断研究，48.5万，2020.06-2021.12，结题，参与（科研秘书）[8] 德国研究基金会项目：Space-Time Dynamics of Extreme Floods (SPATE)，12.8万欧元，2016.12-2018.12，结题，参与（技术骨干）论文专著[1] Yan, J.* and Bárdossy, A. (2019). Short time precipitation estimation using weather radar and surface observations: With rainfall displacement information integrated in a stochastic manner, Journal of Hydrology, 574, 672–682, 2019. (SCI，JCR Q1区, 中科院一区，IF = 6.708)[2] Yan, J.*, Bárdossy, A., Hörning, S., and Tao, T. (2020). Conditional simulation of surface rainfall fields using modified phase annealing, Hydrology and Earth System Sciences (HESS), 24, 2287– 2301. (SCI，JCR Q1, 中科院一区，IF = 6.617)[3] Yan, J., Li, F., Bárdossy, A., and Tao, T.* (2021) Conditional simulation of spatial rainfall fields using random mixing: a study that implements full control over the stochastic process, Hydrology and Earth System Sciences (HESS), 25, 3819–3835. (SCI，JCR Q1, 中科院一区，IF = 6.617)[4] Yan, J. and Tao, T.* (2022). Unsupervised anomaly detection in hourly water demand data using an asymmetric encoder-decoder model, Journal of Hydrology, 613, 128389. (SCI，JCR Q1区, 中科院一区，IF = 6.708)[5] Zhu W., Tao T.*, Yan H., Yan J.*, Wang J., Li S., and Xin K. An optimized LSTM-based approach applied to early warning and forecasting of ponding in the urban drainage system, Hydrology and Earth System Sciences (HESS). (SCI，JCR Q1, 中科院一区，IF = 6.617)[6] Li F. , Yan, J., Yan H., Tao T., Duan H. (2023) 2D Modelling and energy analysis of entrapped air-pocket propagation and spring-like geysering in the drainage pipeline system, Engineering Applications of Computational Fluid Mechanics, 17:1. (SCI，JCR Q1, 中科院一区，IF = 6.1)[7] Chen, L., Yan, H., Yan, J., Wang, J.*, Tao, T., Xin, K., Li, S., Pu, Z., & Qiu, J. (2022). Short-term water demand forecast based on automatic feature extraction by one-dimensional convolution, Journal of Hydrology, 606, 127440. (SCI，JCR Q1区, 中科院一区，IF = 6.708)[8] Li, F.†, Yan, J.†, Xiong, X., Yan, H., *Tao, T. and Wang, L. (2023). GIS-based fuzzy comprehensive evaluation of urban flooding risk with socioeconomic-index system development., Environmental Science and Pollution Research (SCI，JCR Q2区，中科院三区，IF = 5.190)[9] Pu, Z., Yan, J., Li, Z., Chen, L., Tian, W., Xin, K.*, Tao, T. (2023). A hybrid Wavelet-CNN-LSTM Deep Learning model for short-term Urban Water Demand Forecasting, Frontiers of Environmental Science & Engineering. (SCI，JCR Q2区, 中科院二区，IF = 6.048)[10] Yan, Jieru (2018). Nonlinear estimation of short time precipitation using weather radar and surface observations. Universität Stuttgart, Stuttgart. ISBN：978-3-942036-68-9. URL: http:// elib.uni-stuttgart.de/handle/11682/10287. (学术专著)