Sijie Yang
PhD Researcher in NUS Urban Analytics Lab
新加坡国立大学 Urban Analytics Lab 博士研究生
SDE4, CDE
8 Architecture Dr
Singapore 117356
I am Sijie Yang (杨斯捷, pronounced “See-jay Yahng”), a PhD student at Urban Analytics Lab, Department of Architecture, National University of Singapore, where my PhD supervisor is Prof. Filip Biljecki. I hold an MSc in Space Syntax from University College London, a Master of Computer and Information Technology (MCIT) from the University of Pennsylvania, and a Bachelor of Architecture from Chongqing University.
Research has appeared in Landscape and Urban Planning, Building and Environment, Computers, Environment and Urban Systems, Sustainable Cities and Society, and geoinformatics journals such as the ISPRS International Journal of Geo-Information. Workshop papers have been published at top computer science venues such as AAAI and NeurIPS. Professional conference participation includes CUPUM and Space Syntax (the International Space Syntax Symposium).
My research centres on urban comfort, urban liveability, and geospatial intelligence: unifying and quantifying subjective, human-centered perception of the built environment into measurable, city-scale indicators. I develop multimodal learning methods, open tools, and agentic AI systems over multi-source urban data, including street-view and window-view imagery, social media text–image signals, and geospatial data. Current work spans multimodal representation learning and optimization, retrieval-augmented generation and geospatial foundation models, and reasoning-capable AI agents for urban planning and scientific discovery. I aim to advance knowledge in four key areas:
- Urban Intelligence Investigating the integrated development of urban intelligence through emerging technologies, including the Internet of Things (IoT) and artificial intelligence (AI).
- Urban Data Using street-view and window-view imagery, social media text–image signals, and other geospatial data to examine how the built environment and urban dynamics interact.
- Urban Comfort Focusing on subjective, human-centered perceptions of comfort in urban spaces, quantified as measurable, city-scale indicators.
- Architectural Systems Conducting micro-scale investigations into architectural systems, including spatial configurations, building information systems, and sustainable green building solutions.
I am also actively exploring cutting-edge computational methods to advance urban science:
- Foundation Models: Geospatial foundation models and retrieval-augmented generation for reasoning over urban data.
- AI Agents: Reasoning-capable agents for urban planning and scientific discovery.
- World Models: Learning dynamic representations of urban systems for predictive understanding.
- Reinforcement Learning: Enabling adaptive and optimized urban decision-making.
- Spatiotemporal Modeling: Capturing complex geographic patterns across scales and time.
See where this is heading → Horizon.
我是杨斯捷(Sijie Yang,See-jay Yahng),新加坡国立大学建筑系 Urban Analytics Lab 博士研究生,导师为 Filip Biljecki 教授。我拥有伦敦大学学院 Space Syntax 硕士学位、宾夕法尼亚大学计算机与信息技术硕士学位(MCIT),以及重庆大学建筑学学士学位。
研究工作见于 Landscape and Urban Planning、Building and Environment、Computers, Environment and Urban Systems、Sustainable Cities and Society,以及 ISPRS International Journal of Geo-Information 等地理信息期刊。Workshop 论文发表于 AAAI 和 NeurIPS 等计算机科学顶会。专业会议参与包括 CUPUM 和 Space Syntax(International Space Syntax Symposium)。
我的研究聚焦城市舒适、城市宜居与地理空间智能,把建成环境中主观、以人为中心的感知统一并量化为可在城市尺度衡量的指标。我基于街景、窗景、社交媒体图文和地理空间数据等多源城市数据,发展多模态学习方法、开放工具与智能体系统。当前工作包括多模态表征学习与优化、检索增强生成与地理空间基础模型,以及面向城市规划与科学发现的可推理 AI 智能体。聚焦四个方向:
- 城市智能(Urban Intelligence) 探索物联网与人工智能等新兴技术驱动的城市智能一体化发展。
- 城市数据(Urban Data) 利用街景、窗景、社交媒体图文以及其他地理空间数据,分析建成环境与城市动态之间的关联。
- 城市舒适(Urban Comfort) 关注以人为中心的主观舒适感知,并将其量化为可在城市尺度衡量的指标。
- 建筑系统(Architectural Systems) 在微观尺度研究空间配置、建筑信息系统与可持续绿色建筑等议题。
同时,我积极探索前沿计算方法以推进城市科学:
- 基础模型(Foundation Models): 研究地理空间基础模型与检索增强生成,用于城市数据上的推理。
- AI 智能体(AI Agents): 开发面向城市规划与科学发现的可推理智能体。
- 世界模型(World Models): 学习城市系统的动态表征,实现预测性理解。
- 强化学习(Reinforcement Learning): 支持自适应、优化的城市决策。
- 时空建模(Spatiotemporal Modeling): 跨尺度、跨时间捕捉复杂地理模式。
了解研究方向 → Horizon。
featured research精选研究
news动态
| Jul 16, 2026 | Featured on China.com Technology for open-source SP-Survey. See press. 中华网科技 报道开源平台 SP-Survey。详见媒体报道。 |
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| Jul 14, 2026 | Research talk at Prof. Haijing Huang’s group, Chongqing University. Slides. 在重大建规学院 黄海静教授课题组汇报。幻灯片。 |
| Jul 9, 2026 | Featured in China Daily coverage of City Landscape In Sight. See press page. 中国日报 报道 City Landscape In Sight 研究。详见媒体报道。 |
| Jun 13, 2026 | New preprint City Landscape In Sight, window view imagery perception research with Chucai Peng. 新预印本 City Landscape In Sight,与 彭楚才 合作的窗景影像感知研究。 |
| Jun 11, 2026 | Presented StreetRAG-Index poster at 15th Space Syntax Symposium. 在 第15届空间句法研讨会 展示 StreetRAG-Index 海报。 |
| May 9, 2026 | Paper StreetRAG-Index accepted at 15th Space Syntax Symposium. 论文 StreetRAG-Index 被 第15届空间句法研讨会 接收。 |
| Jan 30, 2026 | Visited Mr. Tan Cheng Siong and exchange ideas about future urban development in Singapore and China. 拜访陈成雄先生,就新加坡与中国未来城市发展交流想法。 |
| Jan 26, 2026 | Presented poster Reasoning is All You Need for Urban Planning AI in AAAI 2026 AI4UP workshop. 在 AAAI 2026 AI4UP 研讨会 展示海报 Reasoning is All You Need for Urban Planning AI。 |
| Jan 22, 2026 | Reported research progress to my PhD thesis examiner Assoc. Prof. Yuan Lai from Tsinghua University. 向博士论文考核人、清华大学 赖源副教授 汇报研究进展。 |
| Dec 12, 2025 | Presented my PhD research at NUS-Tsinghua Workshop in Sanya, China 在中国三亚的 NUS-清华研讨会上展示博士研究。 |
| Nov 17, 2025 | Research Reasoning is All You Need for Urban Planning AI accepted by AAAI 2026 AI4UP workshop. 研究 Reasoning is All You Need for Urban Planning AI 被 AAAI 2026 AI4UP 研讨会 接收。 |
| Oct 3, 2025 | Awarded the Tan Cheng Siong Research Scholarship in NUS. 获颁 NUS 陈成雄研究奖学金。 |