李雯欣,女,湖南长沙人,博士,研究生导师。
博士毕业于香港理工大学,硕士毕业于香港科技大学,本科毕业于中南大学。在国际高水平期刊上发表近十篇高质量论文,包括《Sustainable Cities and Society》、《Building and Environment》、《Building Simulation》等期刊。研究聚焦于城市风热环境、微气候调控与韧性低碳城市更新。参与多项香港研究资助局的资助课题。
招收硕士生,诚挚欢迎加入!
研究方向:
多尺度湍流结构的演化机理与降阶算法;
风-热-污染物多场耦合传输与协同调控;
建筑自然通风机制与城市空气质量优化;
人工智能AI优化城市风热环境;
近三年代表性SCI期刊论文:
[1] Li, W., Mak, C.M., Fu, Y., Cai, C., Tse, K.T., Niu, J., & Wong, S.H.Y. (2024). Pedestrian-level wind environment surrounding two tandem non-identical height elevated buildings under the influence of twisted wind flows. Sustainable Cities and Society, 112, 105641. (中科院一区TOP期刊, 影响因子: 12, 第一作者)
[2] Li, W., Mak, C. M., Fu, Y., Cai, C., Tse, K. T., & Niu, J. (2024). The impact of twisted wind on pedestrian comfort around two non-identical-height buildings in tandem arrangement: a wind tunnel study. Building and Environment, 262, 111847. (中科院一区TOP期刊, 影响因子: 7.6, 第一作者)
[3] Li, W., Mak, C. M., Cai, C., Fu, Y., Tse, K. T., & Niu, J. (2024). Wind tunnel measurement of pedestrian-level gust wind flow and comfort around irregular lift-up buildings within simplified urban arrays. Building and Environment, 256, 111487. (中科院一区TOP期刊, 影响因子: 7.6, 第一作者)
[4] Li, W., Mak, C. M., Cai, C. (2025). Mean and turbulent wind characteristics around a high-rise elevated building with curved cross-sections: Wind tunnel experiments and numerical simulations. Building and Environment, 285, 113666. (中科院一区TOP期刊, 影响因子: 7.6, 第一作者)
[5] Li, W., Mak, C. M., Cai, C. (2025). Numerical evaluation of the effect of twist wind on pedestrian comfort surrounding semi-open structures and influential factors under solar heating. Building Simulation. (中科院一区TOP期刊, 影响因子: 5.9, 第一作者)
[6] Fu, Y., Li, C.Y., Zhao, Z., Zhang, B., Tse, K.T., Mak, C.M., Chen, Z., Feng, X., Lin, X., Li, W*., & Lin, C. (2024). Energetic and dynamic characterization of pollutant dispersion in varied building layouts through an augmented analysis procedure. Physics of Fluids, 36 (3). (中科院二区TOP期刊, JCR一区, 影响因子: 4.3, 通讯作者)
[7] Cai, C., Xiao, J., He X., Zou Y., & Li, W*. (2025). Taming Transformers to learn high-resolution partial differential equation distributions via conditional latent diffusion priors. Physics of Fluids, 37 (8). (中科院二区TOP期刊, JCR 一区, 影响因子: 4.3, 通讯作者)
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