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sijie-yang/README.md

👋 Hi, I'm Sijie Yang!

🎓 PhD Student @ Urban Analytics Lab, NUS Architecture, SG
🧑‍💻 CS Master's @ University of Pennsylvania, US
🌏 MSc in Space Syntax (UCL, UK) | B.Arch (Chongqing University, CN)


🌟 About Me

I'm passionate about bridging computer science and GIScience with the built environment. My research explores how emerging technologies can shape smarter, more comfortable cities.
Here’s what drives me:

  • Urban Intelligence: Harnessing IoT & AI for city innovation
  • Urban Data: Analyzing multi-source urban data for real-world impact
  • Urban Comfort: Centering human experience in urban design
  • Architectural Systems: Rethinking buildings for sustainability & intelligence

I am also actively exploring cutting-edge computational methods to advance urban science:

  • Foundation Models: Leveraging large language and vision models for geospatial reasoning
  • 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

🛠️ Tools & Skills

  • Python – my go-to for data analysis and spatial computing
  • QGIS – for mapping, spatial analysis, and beautiful geovisualizations

🚀 Featured Projects

  • thermal-affordance:
    Exploring how urban environments support (or hinder) thermal comfort.

  • streetscape-perception-survey:
    A simple and powerful platform for conducting streetscape perception surveys with image-based questions.

  • urbancode:
    Tools and frameworks for computational urban analysis.


🎵 Hobbies & Fun Facts

  • Music lover (always up for recommendations!)
  • Basketball player & outdoor enthusiast (bike & run)
  • Board game strategist – big fan of Go (the game, not the language 😄)

📈 GitHub Stats

GitHub stats


🤝 Let’s Connect!


Thanks for stopping by my profile! Feel free to reach out, collaborate, or just say hi!

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  1. Thermal-Comfort-In-Sight Thermal-Comfort-In-Sight Public

    The study leverages street view images to understand urban-scale streetscape thermal comfort.

    90 11

  2. City-Landscape-In-Sight City-Landscape-In-Sight Public

    The study leverages real estate imagery to understand urban-scale residential window view perception.

    Jupyter Notebook 9

  3. Urban-Comfort-Potential Urban-Comfort-Potential Public

    Understanding urban comfort from geo-tagged social media posts.

    Jupyter Notebook 10

  4. SP-Survey SP-Survey Public

    A simple and powerful platform for conducting streetscape perception surveys with image-based questions. Deploy in minutes with Supabase and Vercel.

    JavaScript 190 30

  5. SG-Tripcard SG-Tripcard Public

    JavaScript 72 10

  6. Reasoning4UP Reasoning4UP Public

    We introduce the Agentic Urban Planning AI Framework—three cognitive layers (Perception, Foundation, Reasoning) and six logic components (Analysis, Generation, Verification, Evaluation, Collaborati…

    1