Liu Liu

Doctoral Candidate

I am a Ph.D. candidate at MIT in Computational Urban Science, working at the City Form Lab. With eight years of entrepreneurship in data-driven urban analytics, six years of urban design training, and professional experience at China’s top planning institute, my research focuses on the built environment and human behavior analysis through computer vision and AI-driven methods.

Before returning to MIT, I founded CitoryTech Co., Ltd., a start-up specializing in urban visual AI. I have also served as an external expert for Tencent Cloud, a consultant for the World Bank, and an urban researcher at the China Academy of Urban Planning and Design. In addition, I interned as a Ph.D. Applied Scientist at Amazon AGI Foundation, working on the development of large language models (multimodal and text-only) for the past two years.

My academic interests span AI, machine learning, optimization, and urban design research. I am currently completing my dissertation and will be on the academic job market in 2025–2026, seeking faculty opportunities in Urban Science, Urban Planning, and related fields.

Publications

Clarity or confusion: A review of computer vision street attributes in urban studies and planning

Zhou, B., Liu, L., Oliva, A., & Torralba, A.

Recognizing city identity via attribute analysis of geo-tagged images

European conference on computer vision (pp. 519-534)

Liu, L., Zhou, B., Zhao, J., & Ryan, B. D.

C-IMAGE: city cognitive mapping through geo-tagged photos

GeoJournal, 81(6), 817-861

Long, Y., & Liu, L

How green are the streets? An analysis for central areas of Chinese cities using Tencent Street View

PloS one, 12(2), e0171110.

Nicola Colaninno, Rounaq Basu, Maryam Hosseini, Abdulaziz Alhassan, Liu Liu, Andres Sevtsuk

A sidewalk-level urban heat risk assessment framework using pedestrian mobility and urban microclimate modeling

Environment and Planning B: Urban Analytics and City Science

The Recognition of CAZ in Shanghai Based on Evaluated POI. In: Shen Z., Li M. (eds) Big Data Support of Urban Planning and Management

Advances in Geographic Information Science. Springer, Cham

Zhang, Fan, Bolei Zhou, Liu Liu, Yu Liu, Helene H. Fung, Hui Lin, and Carlo Ratti

Measuring human perceptions of a large-scale urban region using machine learning

Landscape and Urban Planning

Liu, Liu, Fan Zhang, Bolei Zhou, Zhoutong Wang, and Yingxin Li

STREETALK: A NAVIGATION SYSTEM FOR PEDESTRIANS AND CYCLISTS

Landscape Architecture Frontiers

Fang, Wanli, Liu Liu, and Jianhao Zhou

Assessing Physical Environment of TOD Communities around Metro Stations: Using Big Data and Machine Learning

Cui, Can, et al.

The spatial-temporal dynamics of daily intercity mobility in the Yangtze River Delta: An analysis using big data

Habitat International

Zhang, D., Yi, H., Chen, Y., Jiang, N., Shao, J., & Liu, L

An urban infrastructure assessment system built on geo-tagged images and machine learning

Computational Urban Science

Colaninno, N., Basu, R., Hosseini, M., Alhassan, A., Liu, L., & Sevtsuk, A

Urban Heat Risk Assessment: Exploring a Novel Pedestrian Network-Based Framework

TRB Annual Meeting

Hosseini, M., Cipriano, M., Eslami, S., Hodczak, D., Liu, L., Sevtsuk, A. and de Melo, G.

ELSA: Evaluating Localization of Social Activities in Urban Streets

arXiv:2406.01551

Liu Liu(Principal Investigator)

Andres Sevtsuk(Co-PI)

Observing the “Sidewalk Ballet”: Leveraging LMMs to Detect Social Interactions in Large-scale Urban Imagery Datasets

Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support, Alexandria, VA, US, Funding Period: January 31, 2025 – January 30, 2026

Contact

10-402

lyons66@mit.edu

Links

CitoryTech Co LTD

Labs