RESEARCH
ADAPTIVE CITIES
The thematic structure and spatial-temporal patterns of building renovation.
POLLEN SCAPE
The impact of urban street tree species on air quality and respiratory illness.
QUANTIFYING PLACES
Analyzing the drivers of pedestrian activity in dense urban environment.
CITY DATA NETWORK
Network analysis on open data and city agency operation.
OPERATION ANALYTICS
Informatics for business improvement district operation with Grand Central Partnership.
NEIGHBORHOOD PROFILE
Quantifying neighborhood growth and data-driven decision support for capital planning.
PREDICTING DENGUE FEVER RISK
Machine learning for spatial epidemiology in Singapore.
FUTURE EMR SYSTEMS
Disrupting Electronic Health Records Systems.
PHYSICAL COMPUTING
Combine Physical Material with Data Computing and Human Movement.
TEAM
Yuan Lai, Ph.D.
Yuan Lai is a Assistant Professor/Special Research Fellow at Tsinghua University. His expertise lies at the intersection of urban information, applied data science, and urban systems. His work has been featured at the United Nations Global Pulse, Bloomberg Technology, Data for Good Exchange, NYC Media Lab, American Planning Association, American Society of Civil Engineers, and Urban Design Forum. Dr. Lai has been leading or participating research projects founded by the National Natural Science Foundation of China (NSFC), National Key Research and Development Program of China，and National Science Foudnation (NSF). Prior to Tsinghua, Dr. Lai was a Lecturer in Urban Science and Planning at MIT Department of Urban Studies and Planning (DUSP) and a research affiliate at NYU Marron Institute of Urban Management and NYU Center for Urban Science and Progress (CUSP). His work involves applied analytics and machine learning using large volume and variety of data related to urban environment, population health, social media, sensing network, and economic transactions. Yuan practiced in urban design at Safdie Architects, where he worked on large scale mixed-use development projects worldwide. He holds a Ph.D. in urban systems and informatics from NYU, a M.S. in Applied Urban Science and Informatics from NYU CUSP, a Master of Urban Planning and a Bachelor of Landscape Architecture. (Faculty Page| LinkedIn |Google Scholar)
Jiatong Li
urban planning|urban health|psychology
Mingyi Ma
smart cities|urban big data|data science
Pokai Zhuang
urban health|future city and community
Jiali Wang
urban planning|smart cities|data science
Guangze Sun
urban planning|urban analytics|urban perception
Seyong Tan
urban management|smart cities and community
Alumni:
Jiachen Zhang (data science, urban computing)
Lan Yan (smart city, mobility|digital economy|automation)
Courses
Introduction to Smart Cities
2023 Spring, Tsinghua
Applied Urban Analytics
2022 Spring, Tsinghua
Applied Data Science for Cities
2021 Spring, MIT
MIT NEET: Digital Cities
2020 Fall, MIT
Applied Data Science for Cities
2020 Spring, MIT
Data Science for Public Good
2019 Winter, MITPUBLICATION
Peer-reviewed Journal Articles
CHUANG PK & LAI, Y.* (2024). Aging-friendly Smart Community Development in China and Data-driven Insights in Beijing[J]. Journal of Chinese Architecture and Urbanism. (Accepted)Ssebyala, S. N., Kintu, T. M., Muganzi, D. J., Dresser, C., Demetres, M. R., Lai, Y., ... & Ghosh, A. K. (2024). Use of machine learning tools to predict health risks from climate-sensitive extreme weather events: A scoping review. PLOS Climate, 3(1), e0000338.
LAI, Y.,* XIA, JY & ZHENG XJ (2023). Smart Human Settlement Theory and Technical Planning Principles from the Perspective of Urban System [J]. Urban Planning, 2023(47):12.
Lai, Y.*, & Lavi, R. (2023). Remote Teaching for Collaboration and Creative Problem-Solving Skills in Undergraduate Urban Science: A Case Study. Journal of Education Studies, 51(4), EDUCU5104001-18.
Liu, Y., & Lai, Y.* (2023). Analyzing jogging activity patterns and adaptation to public health regulation. Environment and Planning B: Urban Analytics and City Science, 23998083231193484.
Lai, Y. & Anni H. (2023) Urban analytics based on human actiVity data: Practical experience of New York City and insights in urban ergonomics. World Architecture, 7(397), 10-16. (in Chinese)
Lai, Y.* , Tang, Y., An J. et al. (2023). Regeneration paths based on endogenous development for old residential neighborhood adjacent to urban shopping district: A design proposal in Xinjiekou, Nanjing. Urban Design, 3: 88-97.(in Chinese)
Watson, H., Gallifant, J., Lai, Y., Radunsky, A. P., Villanueva, C., Martinez, N., ... & Celi, L. A. (2023). Delivering on NIH data sharing requirements: avoiding Open Data in Appearance Only. BMJ Health & Care Informatics, 30(1), e100771.
Lai Y.* & Li J. T. (2023) Integrated multi-scale urban health data analytics based on residents’ activities. Journal of Human Settlements in West China, 38(2): 8-16. (in Chinese)
Lai Y.* & Pokai, Z. (2023) Value proposition of smart city planning under the concept of people's city. Beijing Planning Review, 02:20-24. (in Chinese)
Lai, Y.* , Li, J., Zhang, J., Yan, L., & Liu, Y. (2022). Do vibrant places promote active living? Analyzing local vibrancy, running activity, and real estate prices in Beijing. International Journal of Environmental Research and Public Health, 19(24), 16382.
Lai, Y. (2022). Urban intelligence for carbon neutral cities: Creating synergy among data, analytics, and climate actions. Sustainability, 14(12), 7286.
Lai, Y., Papadopoulos, S., Fuerst, F., Pivo, G., Sagi, J., & Kontokosta, C. E. (2022). Building retrofit hurdle rates and risk aversion in energy efficiency investments. Applied Energy, 306, 118048.
Lai, Y. (2021). Urban intelligence for planetary health. Earth, 2(4), 972-979.
Kontokosta, C. E., Freeman, L., & Lai, Y. (2021). Up-and-coming or down-and-out? Social media popularity as an indicator of neighborhood change. Journal of Planning Education and Research, 0739456X21998445.
Lai, Y. (2021). Urban informatics for green infrastructure: An integrated approach for street trees data collection, analytics, and citizen science in New York City. Landscape Architecture, 28(1), 17-30.
Lai, Y., Charpignon, M. L., Ebner, D. K., & Celi, L. A. (2020). Unsupervised learning for county-level typological classification for COVID-19 research. Intelligence-based medicine, 1, 100002.
Luo, E. M., Newman, S., Amat, M., Charpignon, M. L., Duralde, E. R., Jain, S., ... & Celi, L. A. (2021). MIT COVID-19 Datathon: data without boundaries.BMJ innovations. 7(1):1–4.
Lai, Y., Yeung, W., & Celi, L. A. (2020). Urban intelligence for pandemic response. JMIR public health and surveillance, 6(2), e18873.
Lai, Y., & Kontokosta, C. E. (2019). Topic modeling to discover the thematic structure and spatial-temporal patterns of building renovation and adaptive reuse in cities. Computers, Environment and Urban Systems, 78, 101383.
Lai, Y., & Kontokosta, C. E. (2019). The impact of urban street tree species on air quality and respiratory illness: A spatial analysis of large-scale, high-resolution urban data. Health & place, 56, 80-87.
Lai, Y., & Kontokosta, C. E. (2018). Quantifying place: Analyzing the drivers of pedestrian activity in dense urban environments. Landscape and Urban Planning, 180, 166-178.
Celi, L. A., Marshall, J. D., Lai, Y., & Stone, D. J. (2015). Disrupting electronic health records systems: the next generation. JMIR medical informatics, 3(4), e4192.
Yin, L., Raja, S., Li, X., Lai, Y., Epstein, L., & Roemmich, J. (2013). Neighbourhood for playing: using GPS, GIS and accelerometry to delineate areas within which youth are physically active. Urban studies, 50(14), 2922-2939.
Peer-reviewed Conference Proceedings
Lavi, R., Cong, C., Lai, Y., Lavallee, J. A., Long, G. L., & Melenbrink, N. (2023, June). The evolution of an interdisciplinary case-based learning first-year course. In 2023 ASEE Annual Conference & Exposition.Lai, Y., & Liu, Y. (2022, March). Computing places and human activity in data-absent informal urban settlements. In 2022 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops) (pp. 478-483). IEEE.
Lai, Y. (2020, March). Hyper-local urban contextual awareness through open data integration. In 2020 IEEE International Conference on Pervasive Computing and Communications Workshops (PerCom Workshops) (pp. 1-6). IEEE.
Khmaissia, F., Haghighi, P. S., Jayaprakash, A., Wu, Z., Papadopoulos, S., Lai, Y., & Nguyen, F. T. (2020). An unsupervised machine learning approach to assess the zip code level impact of covid-19 in nyc. Proceedings of the 2020 International Conference on Machine Learning.
Kontokosta, C., Lai, Y., Bonzak, B., Papadopoulos, S., Hong, B., Johnson, N., & Malik, A. (2018). A dynamic spatial-temporal model of urban carbon emissions for data-driven climate action by cities. Bloomberg Data for Good Exchange 2018, New York, NY.
Lai, Y., & Kontokosta, C. (2017, October). Analyzing the drivers of pedestrian activity at high spatial resolution. In 2017 International Conference on Sustainable Infrastructure: Methodology, ICSI 2017 (pp. 303-314). American Society of Civil Engineers (ASCE). New York, NY.
Lai, Y., & Kontokosta, C. E. (2017). Measuring the impact of urban street trees on air quality and respiratory illness. arXiv preprint arXiv:1710.11046.Proceedings of the Bloomberg Data for Good Exchange 2017, New York, NY.
Peer-reviewed Book Chapters
Lai, Yuan and David J. Stone. 2020. "Integrated data intelligence for urban health," Book Chapter in Data Science and Global Health. Harvard-MIT Health Sciences and Technology. Springer.Lai, Yuan and Constantine E. Kontokosta. 2019. "Urban data mining: Sources, types, and limits," Book Chapter in Urban intelligence: How data and information can Shape urban planning, design, and city operations. London: Routledge. (In contract)
Lai, Yuan, Edward Moseley, Francisco Salgueiro, and David J. Stone. 2016. "Integrating non-clinical data with EHRs" in Secondary Analysis of Electronic Health Records, MIT Critical Data Group, ed. Springer International Publishing AG.
Stone, David J., Justin Rousseau, and Yuan Lai. 2016. "Pulling it all together: Envisioning a data-Driven, ideal care system" in Secondary Analysis of Electronic Health Records, MIT Critical Data Group, ed. Springer International Publishing AG.
News Articles, Technical Report, and Working Paper
Yuan Lai 2020. "How to see the inflection point? Application of data science in public health emergencies." Financial Times China.Kontokosta, Constantine E., Yuan Lai, Sokratis Papadopoulos, Jacob Sagi, Franz Fuerst, and Gary Pivo. 2019. "Estimating office and multifamily building energy retrofit hurdle rates and risk arbitrage in energy efficiency investments." Working Paper for Real EstateResearch Institute & Lawrence Berkeley National Laboratory Research Grant.
Kontokosta, Constantine E., Yuan Lai, Bartosz Bonczak, Sokratis Papadopoulos, Boyeong Hong, Awais Malik, and Nicholas Johnson. 2017. "Urban physiology: A dynamic spatial-temporal model of urban carbon emissions to drive climate action by cities." Technical report for the United Nations Data for Climate Action Challenge.
Yuan Lai, Sreoshy Banerjea, Alison Von Glinow.2017. "Arrival House: How can we redesignand rethink housing to better integrate the arrival of immigrants to their new city?" Tech-nical report for Urban Design Forum Design for Arrival Program.
NYC Department of City Planning Capital Planning Division and NYU Center for Urban Science and Progree, 2016. "Neighborhood Profiles: Planning and Visualizing for Strategic Growth." Technical report for Applied Urban Science and Informatics master capstone project.
Invited Talks, Conference Presentations, and Media Coverage
Panel speaker, "Integrating Urban Open Data for Public Good", Open Data Science Conference (ODSC) East, Boston, MA. Apr 2020.Panel paper presenter, "Using Big Data and Social Media to Understand Neighborhood Conditions", Association for Public Policy Analysis and Management (APPAM) Annual Fall Research Conference. Denver, CO. Nov 8, 2019.
Invited roundtable discussion with American Express, 13th Annual Machine Learning Symposium, The New York Academy of Sciences. New York. Mar 1, 2019.
Guest Lecture, “Urban Informatics and Big Data for Quality-of-Life.” for a graduate course HST.936: Leveraging Data Science in Global Health. Harvard-MIT Health Sciences and Technology (HST). Feb 8, 2019.
“Arrival House: an Integrated Co-Living Model for New Arrivals to NYC”, American Planning Association New York Metro Annual Conference, New York City, November 2018.
“Big Data for Local Climate Change”, MetroLab Network Summit, Newark, October 2018.
“Applied Analytics in Cities”, invited lecture, Taipei Medical University, College of Management Graduate Institute of Data Science, Taipei, October 2018.
“Design for Arrival: A co-live housing scenario”, Urban Design Forum, New York, March 2018.
U.S. Foreign Policy Colloquium 2017: National Committee on United States–China Relations
“Informatics for business improvement district operation: Grand Central Partnership”, conference panel, Bloomberg Data for Good Exchange Immersion Day, Bloomberg L.P., October 2017.
“Data for Good: Bloomberg supports data scientists’ work with nonprofits and municipalities to solve real-world problems” by NYC Media Lab on October 2017.
“Measuring the impact of urban street trees on air quality and respiratory illness”, conference presentation, Bloomberg Data for Good Exchange, October 2017.
“Data interface with AR in future work environment”, Tech at Bloomberg, August 2017.
“Bloomberg AR Fellows Prototype Possible Future for Augmented Reality in the Enterprise”, Tech at Bloomberg, August 2017.
“Analyzing the drivers of pedestrian activity at high spatial resolution”, International Conference on Sustainable Infrastructure, American Society Of Civil Engineers, 2017.
“Urban informatics and interpretable data”, invited lecture, Graduate School of Architecture, Planning and Preservation, Columbia University, February 2017
“Students Develop Tech Ideas into Reality at HackNYU 2016”, featured in NYU, March 2016
“Urban Design with Big Data”, invited presentation, MIT Senseable City Lab, July 2014.