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sijie-yang/README.md

πŸ‘‹ Hi, I'm Sijie Yang!

πŸŽ“ PhD Student @ Urban Analytics Lab, NUS Architecture, SG
πŸ§‘β€πŸ’» 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

πŸ› οΈ Tools & Skills

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

πŸš€ 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 πŸ˜„)

πŸ“ˆ 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.

    87 11

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

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

    Jupyter Notebook 7

  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 178 30

  5. Awesome-Urban-AI Awesome-Urban-AI Public

    Jupyter Notebook

  6. SG-Tripcard SG-Tripcard Public

    JavaScript 72 10