研究与教学方向
城市社会学
建筑调研方法和理论
城市更新
机器学习在城市研究中的应用
电子邮箱：jiaxin.arch@ncu.edu.cn
教育简历
南昌大学建筑与工程学院，建筑学学士，2016年
东南大学建筑学院，建筑学硕士，2019年
大阪大学能源与环境学院，工学博士，2022年
大阪大学环境设计与信息技术实验室，特聘研究员，2022年11月至今
科研项目
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）”
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
获奖
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
第五届2014年高等院校“斯维尔”杯BIM建模大赛建筑节能及日照分析专项一等奖
学术兼职
Geo-spatial Information Science (SCI), Buildings (SCI), ISPRS International Journal of Geo-Information (SCI), Sustainability (SCI), Applied Sciences (SCI), Energies (SCI), Journal of Asian Architecture and Building Engineering (SCI)审稿人。
发表论文
Kuang, Z., Zhang, J., Huang, Y., & Li, Y. Advancing Urban Renewal: An Automated Approach to Generating Historical Arcade Facades with Stable Diffusion Models. HABITS OF THE ANTHROPOCENE - Proceedings of the 43rd ACADIA Conference - Volume II: Proceedings book one, University of Colorado, Denver, USA, 26-28 October 2023, pp. 616-625. (EI会议)
Zhang, J., Hu, J., Zhang, X., Li, Y., & Huang, J. (2023). Towards a Fairer Green city: measuring unfairness in daily accessible greenery in Chengdu’s Central city. Journal of Asian Architecture and Building Engineering, (SCI, JCR Q4, IF:1.3).
Zhang, J., Yu, Z., Li, Y., & Wang, X. (2023). Uncovering Bias in Objective Mapping and Subjective Perception of Urban Building Functionality: A Machine Learning Approach to Urban Spatial Perception. Land, 12(7), 1322.（SCI, JCR Q2, IF: 3.9）
Zhang, J., Fukuda, T., & Yabuki, N., Li Y. (2023) SYNTHESIZING STYLE-SIMILAR RESIDENTIAL FACADE FROM SEMANTIC LABELING ACCORDING TO THE USER-PROVIDED EXAMPLE. CAADRIA2023 (EI会议)
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, JCR Q1, IF: 6.167)
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, JCR Q1, IF: 6.263)
Ma, K.*, Wang, B., Li, Y., & Zhang, J. (2022). Image Retrieval for Local Architectural Heritage Recommendation Based on Deep Hashing. Buildings, 12(6), 809. (SCI, JCR Q2, IF: 3.324)
Tang, Y., Zhang, J., Liu, R.*, & Li, Y. (2022). Exploring the Impact of Built Environment Attributes on Social Followings Using Social Media Data and Deep Learning. ISPRS International Journal of Geo-Information, 11(6), 325. (SCI, JCR Q2, IF: 3.1)
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, JCR Q2, IF: 4.342)
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, JCR Q2, IF: 3.1)
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)
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.
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). (EI会议)
Li, Y., Zhang, J., & Yu, C. (2019, April). Intelligent Multi-Objective Optimization Method for Complex Building Layout based on Pedestrian Flow Organization-A case study of People's Court building in Anhui, China. 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（EI会议）
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（EI会议）
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.（CSSCI）
钱坤, 于长江, 张嘉新, & 李海清*. (2017). 基于被动式新风技术的中国霍夫曼窑改造与再利用初探——以高淳蒋山村霍夫曼窑为例. 城市建筑, (10), 36-39.