助理教授/特别研究员，博士生导师
E-mail：yuanlai@tsinghua.edu.cn
【研究和教学方向】
城市科学、城市信息学、城市设计、智慧城市、城市健康
【教育经历】
2016-2019，美国纽约大学土木与城市工程系，工学博士（城市系统与信息学方向）
2015-2016，美国纽约大学城市科学与发展中心，理学硕士（应用城市科学与信息学专业）
2009-2011，美国纽约州立大学布法罗分校，城市规划学硕士 （城市设计与地理信息系统方向）
2005-2009，北京林业大学，风景园林学士
【专业履历】
2021.6-至今， 清华大学建筑学院城市规划系，助理教授/特别研究员，博士生导师
2019.8-2021.5，美国麻省理工学院城市研究与规划系(MIT DUSP)，讲师 (城市科学方向)
2018.9-2019.5，美国纽约大学城市管理研究所 (NYU Marron Institute)，研究助理
2016.7-2018.7，美国纽约大学城市科学与发展中心 (NYU CUSP)，研究助理
2011.7-2015.8，美国萨夫迪建筑设计事务所（波士顿），城市设计师
【讲授课程】
本科生课程：城市设计；城乡规划基础（8）
研究生课程：城市信息学I-城市应用分析；城市信息学II-智慧城市导论
【学术兼职】
自然资源部 智慧人居环境与空间规划治理技术创新中心 技术带头人、副秘书长
中国城市科学研究会 数字孪生与未来城市专委会，委员
中国城市规划学会 规划实施分会，青年委员
美国城市设计论坛 (Urban Design Forum) 委员会成员
纽约大学城市管理研究所研究学者
国际电气电机工程师协会 (IEEE) 会员
国际期刊PLOS Digital Health 副主编（Associate Editor）
Landscape and Urban Planning, Urban Studies, Health & Place, ACM Transactions on Spatial Algorithms and Systems, Sustainable Cities and Society, Data & Policy, Informatics等期刊审稿人
【主要研究课题】
1. 国家自然科学基金项目“基于居民活动的城市空间柔性测度与评估研究”，2023-2026（负责人）
2. 国家重点研发计划课题子任务“多源数据高精度融合技术研究”，2022-2025 （负责人）
3. 北京卓越青年科学家计划“北京城乡土地利用优化的理论、规划方法和技术体系研究”开放课题“基于多源数据的北京房地产资源分布与社区活力分析”，2021-2022（负责人）
4. 美国国家科学基金项目“智能和可持续城市的城市信息学以及数据驱动的理论研究”，2017-2019（项目骨干2/10）
5. 美国劳伦斯-伯克利国家实验室(LBNL)与美国房地产研究所(RERI)联合研究课题“城市信息学应用于建筑改造与能源效率投资分析”，2018-2021（项目骨干2/10）
6. 美国彭博资讯科技原型设计研发项目“增强现实数据界面在未来办公空间应用”，2017-2017（负责人）
【荣誉及获奖】
2023，第七届“城垣杯”规划决策支持模型设计大赛 优秀奖（指导教师）
2021，首届全国大学生国土空间规划设计竞赛 二等奖（指导教师）
2021，首届全国大学生国土空间规划设计竞赛 最佳立意奖（指导教师）
2019，谷歌人工智能社会影响挑战优胜团队
2018，联合国大数据应对气候变化行动挑战最佳数据可视化奖
2017，彭博资讯Bloomberg Data for Good Exchange数据科学家奖
2017，美国城市设计论坛前沿学者
2017，彭博资讯与纽约多媒体实验室（NYC Media Lab）增强现实技术研发学者
2016，纽约大学校园数据信息开发竞赛优胜团队
2015，纽约大学学术奖学金
2014，麻省理工学院医疗信息与数据分析竞赛第二名
2011，纽约州立大学布法罗分校建筑与城市规划学院，最佳毕业论文
2011，美国规划师协会（APA）纽约州分会优秀学生项目奖
【部分学术出版】
期刊论文
1. LIU Y, LAI Y. Analyzing jogging activity patterns and adaptation to public health regulation[J]. Environment and Planning B: Urban Analytics and City Science, 2024,51(3): 670-688.
2. 来源, 郑筱津, 夏静怡. 城市系统视角的智慧人居理论与技术规划原则[J].城市规划, 2023,47(12):89-96.
3. LAI Y, LAVI R. Remote Teaching for Collaboration and Creative Problem-Solving Skills in Undergraduate Urban Science: A Case Study [J]. Journal of Education Studies, 2023,51(4): EDUCU5104001.
4. 来源, 胡安妮. 基于人居活动数据的城市分析——纽约市实践经验及其城市人因工程学启示[J].世界建筑, 2023, 7(397): 10-16.
5. 来源, 李佳彤.基于居民活动的多尺度城市健康数据融合分析[J].西部人居环境学刊, 2023, 38(2): 8-16.
6. 来源，庄博凯.人民城市理念下的智慧城市规划价值导向思考[J].北京规划建设, 2023, 209: 20-25.
7. WATSON H, JACK GALLIFANT, YUAN LAI, et al. Delivering on NIH data sharing requirements: avoiding Open Data in Appearance Only[J]. BMJ Health & Care Informatics, 2023, 30(1): e100771.
8. LAI Y, LI J, ZHANG J, et al. Do vibrant places promote active living? Analyzing local vibrancy, running activity, and real estate prices in Beijing[J]. International Journal of Environmental Research and Public Health, 2022, 19: 16382.
9. LAI Y, PAPADOPOULOS S, FUERST F, et al. Building retrofit hurdle rates and risk aversion in energy efficiency investments[J]. Applied Energy, 2022, 306: 118048.
10. LAI Y. Urban Intelligence for Carbon Neutral Cities: Creating Synergy among Data, Analytics, and Climate Actions[J]. Sustainability, 2022, 14(12).
11. LAI Y. Urban Intelligence for Planetary Health[J]. Earth, 2021, 2(4): 972-9.
12. KONTOKOSTA C E, FREEMAN L, LAI Y. Up-and-Coming or Down-and-Out? Social Media Popularity as an Indicator of Neighborhood Change[J]. Journal of Planning Education and Research, 2021: 0739456X21998445.
13. 来源, 王钰, 林添怿. 面向绿色基础设施的城市信息学:纽约市行道树数据收集、分析与公众科学的综合研究[J]. 风景园林, 2021, 28(1): 17-30.
14. LAI Y, CHARPIGNON M L, EBNER D K, et al. Unsupervised learning for county-level typological classification for COVID-19 research [J]. Intell Based Med, 2020, 1: 100002.
15. LUO E M, NEWMAN S, AMAT M, et al. MIT COVID-19 Datathon: data without boundaries [J]. BMJ Innov., 2021, 7(1): 231-4.
16. LAI Y, YEUNG W, CELI L A. Urban Intelligence for Pandemic Response: Viewpoint [J]. JMIR Public Health Surveill., 2020, 6(2): e18873.
17. LAI Y, KONTOKOSTA C E. Topic modeling to discover the thematic structure and spatial-temporal patterns of building renovation and adaptive reuse in cities [J]. Computers, Environment and Urban Systems, 2019, 78: 101383.
18. LAI Y, KONTOKOSTA C E. The impact of urban street tree species on air quality and respiratory illness: A spatial analysis of large-scale, high-resolution urban data. [J]. Health & place, 2019, 56: 80-7.
19. LAI Y, KONTOKOSTA C E. Quantifying place: Analyzing the drivers of pedestrian activity in dense urban environments [J]. Landscape and Urban Planning, 2018, 180: 166-78.
20. CELI L A, MARSHALL J D, LAI Y, et al. Disrupting Electronic Health Records Systems: The Next Generation [J]. JMIR Med Inform, 2015, 3(4): e34.
21. YIN L, RAJA S, LI X, et al. Neighbourhood for Playing: Using GPS, GIS and Accelerometry to Delineate Areas within which Youth are Physically Active [J]. Urban Studies, 2013, 50(14): 2922-39.
学术著作
1. 来源. 城市信息与数据科学导论：智慧城市系统构造与应用 [M]. 北京: 中国建筑工业出版社, 2022.
2. LAI Y, STONE D J. Data Integration for Urban Health [M]//AL. L A C E. Leveraging Data Science for Global Health. Springer. 2020: 351-63.
3. LAI Y, MOSELEY E, SALGUEIRO F, et al. Integrating Non-clinical Data with EHRs [M]//DATA M C. Secondary Analysis of Electronic Health Records. Springer. 2016: 51-60.
4. STONE D J, ROUSSEAU J, LAI Y. Pulling It All Together: Envisioning a Data-Driven, Ideal Care System [M]//DATA M C. Secondary Analysis of Electronic Health Records. Springer. 2016: 27-42.
会议论文
1. LAVI R, CONG C, LAI Y, et al. The Evolution of an Interdisciplinary Case-Based Learning First-Year Course [Z]. 2023 ASEE Annual Conference & Exposition. 2023
1. Lai, Y., Liu Y.F. 2022, March. Computing places and human activity in data-absent informal urban settlements. In 2022 IEEE International Conference on Pervasive Computing and Communications Workshops (Pervasive Smart Sustainable Cities Workshops),IEEE.
2. Khmaissia, F., Sagheb Haghighi, P., Jayaprakash, A., Wu, Z., Papadopoulos, S., Lai, Y. and Nguyen, F.T., 2020. An unsupervised machine learning approach to assess the ZIP code level impact of COVID-19 in NYC. In 2020 International Conference on Machine Learning, Healthcare Systems, Population Health, and the Role of Health-Tech.
3. 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.
4. Kontokosta, C.E., Lance, F. and Lai, Y., 2019. Using big data and social media to understand neighborhood Conditions. In Association for Public Policy Analysis and Management Annual Research Conference.
5. Kontokosta, C. E., Lai, Y., Bonczak, B., Papadopoulos, S., Hong, B., Malik, A. and Johnson, N., 2018. A dynamic spatial-temporal model of urban carbon emissions for data-driven climate action by cities. Proceedings of the 2018 Bloomberg Data for Good Exchange, New York, NY.
6. Lai, Y. and Kontokosta, C. E., 2017. Analyzing the drivers of pedestrian activity at high spatial resolution. American Society of Civil Engineers (ASCE) International Conference on Sustainable Infrastructure, New York, NY.
7. Lai, Y. and Kontokosta, C. E., 2017. Measuring the impact of urban street trees on air quality and respiratory illness: A data-driven approach to environmental justice. Proceedings of the 2107 Bloomberg Data for Good Exchange, New York, NY.
项目报告
1. Avasarala, S., Chen, S., Counts, S., Fink, J., Fulton, B., Gordon, E., Harlow, J., Hodgson, P., Lai, Y., Merida, W., O’Brien, D. and Shelton, K., 2020. How cities can become more flexible in the wake of COVID-19: Housing case study. Microsoft Research.
2. Kontokosta, C., Lai, Y., Papadopoulos, S., Sagi, J., Fuerst, F. and Pivo, G., 2019. Estimating office and multifamily building energy retrofit hurdle rates and risk arbitrage in energy efficiency investments. Working paper for Real Estate Research Institute & Lawrence Berkeley National Laboratory Research Grant.
3. Lai, Y., Glinow, A.V. and Banerjea, S., 2018. Arrival House: How can we redesign and rethink housing to better integrate the arrival of immigrants to their new city? Design research report for Urban Design Forum Design for Arrival Program.
4. Kontokosta, C., Lai, Y., Bonczak, B., Papadopoulos, S., Hong, B., Malik, A. and Johnson, N., 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.
5. NYC Department of City Planning and NYU CUSP. 2016. Neighborhood profiles: Planning and visualizing for strategic growth. Technical report for urban science and informatics capstone project.
特邀报告与媒体报道
1. Lai, Y. and Levi, R. Perspectives from New Engineering Education Transformation on Curriculum Transformation. MIT J-WEL Higher Education Workshop, Cambridge, 2020.
2. Media coverage, What is the Covid-19 data tsunami telling policymakers? A global team of researchers searches for insights during a weeklong virtual “datathon.” MIT News, 2020.
3. Lai, Y. Integrating urban open data for public good. Open Data Science Conference, Boston, 2020.
4. Lai, Y. Using big data and social media to understand neighborhood conditions. Association for Public Policy Analysis and Management (APPAM) Annual Research Conference, Denver, 2019.
5. Media coverage: Exploring urban science. MIT News, 2019.
6. Lai, Y., Glinow, A.V. and Banerjea, S. Arrival house: An integrated co-living model for new arrivals to NYC”, National Organization of Minority Architects (NOMA) Annual Conference, New York, 2019.
7. Lai, Y., Glinow, A.V. and Banerjea, S. Community-based co-living in NYC. New York Build Expo, New York, 2019.
8. Lai, Y. Invited roundtable discussion with American Express, 13th Annual Machine Learning Symposium, The New York Academy of Sciences, New York, 2019.
9. Media coverage: New York City’s pollen scape, and what it says about air quality & environmental justice. Marron Institute of Urban Management, 2019.
10. Lai, Y., Glinow, A.V. and Banerjea, S. Arrival house: An integrated co-living model for new arrivals to NYC. American Planning Association New York Metro Annual Conference, New York, 2018.
11. Lai, Y. Big data for local climate change. MetroLab Network Summit, Newark, 2018.
12. Lai, Y., Glinow, A.V. and Banerjea, S. Design for arrival: A co-live scenario for newly arrived immigrants to New York City. Urban Design Forum, New York, 2018.
13. Media coverage: “Data for good: Bloomberg supports data scientists work with nonprofits and municipalities to solve real-world problems”. NYC Media Lab, 2017.
14. Lai, Y. Analyzing the drivers of pedestrian activity at high spatial resolution. American Society of Civil Engineers (ASCE) International Conference on Sustainable Infrastructure, New York, 2017.
