Xiao Wang

王笑

wangxiao_seu@seu.edu.cn

Xiao Wang is a Postdoctoral Research Fellow at Laboratory of Architectural Algorithm and Application (Lab. AAA), Southeast University, supervised by Prof. Peng Tang. His primary research interests include the digital conservation and renewal design of historic areas, the construction and application of knowledge models for historic areas, and generative architecture and urban design. He has awarded a fellowship from the China Postdoctoral Science Foundation, and participated in one National Key R&D Program and two General Projects of the NSFC. Projects he contributed to have received the 2024 UNESCO Asia-Pacific Awards for Cultural Heritage Conservation—Award of Excellence and Special Recognition for Sustainable Development, the Second Prize in the Conservation and Innovation Category of the 2019–2020 Architectural Design Awards of the Architectural Society of China, and have been exhibited at the 2016 Venice Architecture Biennale Collateral Exhibition.

王笑，东南大学建筑学院建筑运算与应用实验室（Lab. AAA）博士后助理研究员，合作导师唐芃教授。主要研究方向为历史地段的数字化保护与更新设计、历史地段知识模型建构与应用、生成式建筑与城市设计等。主持中国博士后科学基金面上项目1项，参与国家重点研发计划1项、国家自然科学基金面上项目2项。参与完成项目获2024年度联合国教科文组织亚太遗产保护奖杰出项目奖与可持续发展特别表彰奖、2019-2020中国建筑学会建筑设计奖历史文化保护传承创新类二等奖，参展2016威尼斯建筑双年展平行展等。

Education

2020/04–2025/03, SEU, Ph.D. in Architecture
2022/11–2023/08, ETH Zurich, Visiting Ph.D. Student
2015/09–2018/06, SEU, M.Eng. in Architecture
2010/09–2014/06, HIT, B.Eng. in Civil Engineering & B.Eng. in Engineering Management

2020/04–2025/03，东南大学，建筑学工学博士
2022/11–2023/08，苏黎世联邦理工学院，联合培养博士生
2015/09–2018/06，东南大学，建筑学工学硕士
2010/09–2014/06，哈尔滨工业大学，土木工程工学学士、工程管理工学学士（双学位）

Research

General Program of China Postdoctoral Science Foundation, 2025M771613, Research on Artificial Intelligence-Driven Methods for Feature Representation and Renewal Design in Historic Areas, 2025/07–2027/06, Ongoing, PI
Postgraduate Research Innovation Program of Jiangsu Province, KYCX21_0110, Data-driven Analysis of Spatial Morphology and Generative Design of Historic Areas, 2021/06–2024/04, Completed, PI

中国博士后科学基金面上项目，2025M771613，人工智能驱动的历史地段风貌特征表述和更新设计方法研究，2025/07-2027/06，在研，主持
江苏省研究生科研创新计划，KYCX21_0110，数据驱动的历史地段空间形态分析与生成设计，2021/06-2024/04，已结题，主持

Publications

王笑, 朱雪融, 唐芃. 中国传统村落特征的解读与集群识别——基于聚类和知识图谱的认知与利用方法[J]. 建筑学报, 2025, (04): 82–89.
Wang, X., Song, Y., Tang, P. Generative urban design using shape grammar and block morphological analysis [J]. Frontiers of Architectural Research, 2020, 9(4): 914–924.
唐芃, 王笑, 李金泽, 宋哲昊. “形—量—形”视角下历史地段的保护与更新[J]. 世界建筑, 2022, (11): 58–59.
唐芃, 王笑, 李金泽. 历史地段多尺度层级形态中的数字化解析及设计应用[J]. 城市环境设计, 2022, (01): 250–257.
唐芃, 王笑, 华好. 解码历史——宜兴丁蜀古南街历史风貌保护与更新中的数字技术与实践[J]. 建筑学报, 2021, (05): 24–30.
Tang, P., Wang, X., Shi, X. Generative design method of the facade of traditional architecture and settlement based on knowledge discovery and digital generation: a case study of Gunanjie Street in China [J]. International Journal of Architectural Heritage, 2019, 13(5): 679–690.

Wang, X., Zhu, X., Tang, P. Characterization of The Chinese Traditional Villages Based on The Morphological Clustering and Knowledge Graph [C] // ACCELERATED DESIGN – Proceedings of the 29th CAADRIA Conference, Singapore, 20–26 April 2024, 263–272.
Wang, X., Tang, P., Cai, C. Traditional Chinese Village Morphological Feature Extraction and Cluster Analysis Based on Multi-source Data and Machine Learning [C] // Proceedings of the 28th CAADRIA Conference, Ahmedabad, India, 18–24 March 2023, 179–188.
Wang, X., Tang, P. Case Study of Collaborative Urban Design based on Generative Modeling and Simulation [C] // Proceedings of SimAUD 2020, Vienna, Austria, 25–27 May 2020, 179–186.
王笑, 唐芃, 宋亚程. 基于街区形态复杂性的生成语法表述与应用——以南京城区为例 [C] // 设计的溯源与未来——2020计算性设计国际学术论坛暨中国建筑学会计算性设计学术委员会年会论文集. 哈尔滨, 中国, 2020年12月, 278–288.
Wang, X., Tang, P., Shi, X. Analysis and conservation methods of traditional architecture and settlement based on knowledge discovery and digital generation: case study of Gunanjie Street in China [C] // Proceedings of the 24th CAADRIA Conference, Wellington, New Zealand, 15–18 April 2019, 757–766.
Wang, X., Tang, P., Shi, X. Building facade description system and historical feature analysis method by rough set theory and algorithmic language: a case study on the traditional architecture and settlements in Gunanjie Street, Yixing, China [C] // Proceedings of iaSU 2016, Nishinomiya, Japan, 16–18 July 2016, 179–185.