姓        名：张嘉新
职务职称：讲师
电子邮箱：jiaxin.arch@ncu.edu.cn
研究方向：计算机辅助建筑与城市设计
主讲课程:《建筑调研方法与理论》、《城市社会学》、《建筑设计基础1》等
研究成果：

科研项目：

l 参与国家社会科学基金一般项目“中国近现代建筑技术史研究（15BZS089）”

l 参与日本学术振兴会（JSPS）一般基础研究“开发一个使用深度学习估计环境的环境设计支持混合现实系统”，基金号JP19K12681

论文：

l Zhang, J., Fukuda, T.*, &Yabuki, N. (2022). Automatic Generation of Synthetic Datasets from a City Digital Twin for use in the Instance Segmentation of Building Facades. Journal of computational design and engineering. (SCI, JCRQ1)

l Hu, J., Zhang, J.*, & Li, Y. (2022). Exploring the spatial and temporal driving mechanisms of landscape patterns on habitat quality in a city undergoing rapid urbanization based on GTWR and MGWR: The case of Nanjing, China. Ecological Indicators, 143, 109333. (SCI, JCRQ1)

l Zhang, J., Fukuda, T.*, &Yabuki, N. (2021). Automatic Object Removal with Obstructed Facades Completion using Semantic Segmentation and Generative Adversarial Inpainting. IEEE Access, 9, 117486-117495. (SCI, JCRQ2)

l Zhang, J., Fukuda, T.*, &Yabuki, N. (2021). Development of a City-Scale Approach for Façade Color Measurement with Building Functional Classification Using Deep Learning and Street View Images. ISPRS International Journal of Geo-Information, 10(8), 551. (SCI, JCRQ2)

l Zhang, J., Fukuda, T., &Yabuki, N. (2021, April). Image-based Landscape Simulation with Automatic Object Removal and Facade Inpainting Using Semantic Segmentation and Generative Adversarial Networks. SimAUD 2021 (Symposium on Simulation for Architecture and Urban Design)

l Zhang, J., Fukuda, T., &Yabuki, N. (2020, July). A Large-Scale Measurement and Quantitative Analysis Method of Façade Color in the Urban Street Using Deep Learning. The International Conference on Computational Design and Robotic Fabrication (CDRF2020) (pp. 93-102). Springer, Singapore.

l Li, Y., Yabuki, N., Fukuda, T., & Zhang, J. (2020, September). A big data evaluation of urban street walkability using deep learning and environmental sensors-a case study around Osaka University Suita campus. (eCAADe 2020).

l Zhang, J., Li, Y., Li, H., & Wang, X. (2019, April). Sensitivity Analysis of Thermal Performance of Granary Building based on Machine Learning. 亚洲计算机辅助建筑设计研究协会 24 届年会（CAADRIA 2019）, 惠灵顿，新西兰，2019年4月

l 李海清*, 于长江, 钱坤, & 张嘉新. (2017). 易建性: 作为环境调控与建造模式之间的必要张力——一个关于中国霍夫曼窑之建筑学价值的案例研究. 建筑学报, (7), 8-13.

获奖：

l 第三届2017年“中国人居环境设计教育年会暨学年奖”建筑设计组铜奖