Jingrong Zhang | 张镜荣

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Jingrong’s work explores the intersection of art, design, science, and cities, with a focus on social behavior in public spaces, racial and gender equity, and urban greenery and biodiversity. Her projects have been featured and supported by the Council for the Arts at MIT, World Economic Forum, Venice Biennale, and Shanghai Library. Trained in urban planning, she holds a master’s degree in Applied Urban Science and Informatics from New York University’s Center for Urban Science and Progress.  


< Home >

• + Street Scores 
  
• + Dust Bloom 
  
• + Tree-D Fusion  
  
• + Beijing Inside Out 
  
• + Senseable Global Labs 
  
• 
  
• + The Electric Commute 
  
• + Word as Image 
  
• + In Search of Authenticity 
  

Email: jingrong.zhang@nyu.edu 

CV  

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Experience  Research Fellow
MIT Senseable City Lab 
2023 - present

GIS and Mapping Specialist
Data Services, NYU Division of Libraries 
2022 - 2023

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EducationNew York University
MS in Applied Urban Science and Informatics
2022

Tianjin University
BEng in Urban Planning 
2020  

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ExhibitionStreet Scores
Interactive Installation & Performance, MIT Open Space  
2025 

Eyes on the Street
19th International Architecture Exhibition, La Biennale di Venezia 2025 

Re-Leaf
19th International Architecture Exhibition, La Biennale di Venezia 2025 

Word as Image 
Shanghai Library  
2023  

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Talks   Visual Empathy in the Age of Data
Data | Art Symposium, Harvard University
2025

Visualizing Seshat: Unveiling Patterns in Human History with Seshat Databank
Complexity Science Hub
2024

The Electric Commute: Envisioning 100% Electrified Mobility in NYC
NYC Open Data Week  
2023

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Services  
NYC Open Data Ambassador Trainee

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[Beijing Inside Out]
 

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About   In Beijing Inside Out, we explore how broad urban and socio-political policies impact individual domestic spaces in Beijing. Using a computer-vision methodology to analyze floor plans of over 2,000 apartments built between 1970 and 2020, we calculated the distribution, intensity, and nature of domestic activities, controlling for property size and age. Our findings reveal an increasing intensity of living rooms, dining rooms, and kitchens, indicating a shift toward greater privacy and mixed-use spaces. This study highlights the potential of integrating large-scale imagery data with computer vision technology to generate profound insights into architectural and domestic studies.

Explore at https://senseable.mit.edu/beijing-inside-out/ 

Contribution: visualization, storytelling