來源
副教授/特别研究員，博士生導師
E-mail：yuanlai@tsinghua.edu.cn
【研究和教學方向】
城市信息學、城市設計、智慧城市、城市健康
【教育經曆】
2016-2019，美國紐約大學土木與城市工程系，工學博士（城市系統與信息學方向）
2015-2016，美國紐約大學城市科學與發展中心，理學碩士（應用城市科學與信息學專業）
2009-2011，美國紐約州立大學布法羅分校，城市規劃學碩士 （城市設計與地理信息系統方向）
2005-2009，北京林業大學，風景園林學士
【專業履曆】
2024.7-至今， beat365城市規劃系，副教授/特别研究員，博士生導師
2021.6-2024.6，beat365城市規劃系，助理教授/特别研究員，博士生導師
2019.8-2021.5，美國麻省理工學院城市研究與規劃系(MIT DUSP)，講師 (城市科學方向)
2018.9-2019.5，美國紐約大學城市管理研究所 (NYU Marron Institute)，研究助理
2016.7-2018.7，美國紐約大學城市科學與發展中心 (NYU CUSP)，研究助理
2011.7-2015.8，美國薩夫迪建築設計事務所（波士頓），城市設計師
【講授課程】
本科生課程：城市設計；城鄉規劃基礎
研究生課程：城市信息學I-城市應用分析；城市信息學II-智慧城市導論
【學術兼職】
自然資源部 智慧人居環境與空間規劃治理技術創新中心 副秘書長，技術帶頭人
中國城市科學研究會 數字孿生與未來城市專委會 副秘書長，委員
中國城市規劃學會規劃實施分會，青年委員
美國城市設計論壇 (Urban Design Forum) 委員會成員
紐約大學城市管理研究所研究學者
國際電氣電機工程師協會 (IEEE) 會員
國際期刊PLOS Digital Health 副主編（Associate Editor）
Landscape and Urban Planning, Urban Studies, Health & Place, ACM Transactions on Spatial Algorithms and Systems, Sustainable Cities and Society, Data & Policy, Informatics等期刊審稿人
【主要研究課題】
1. 國家自然科學基金項目“基于居民活動的城市空間柔性測度與評估研究”，2023-2026（負責人）
2. 國家重點研發計劃課題子任務“多源數據高精度融合技術研究”，2022-2025 （負責人）
3. 北京卓越青年科學家計劃“北京城鄉土地利用優化的理論、規劃方法和技術體系研究”開放課題“基于多源數據的北京房地産資源分布與社區活力分析”，2021-2022（負責人）
4. 美國國家科學基金項目“智能和可持續城市的城市信息學以及數據驅動的理論研究”，2017-2019（項目骨幹2/10）
5. 美國勞倫斯-伯克利國家實驗室(LBNL)與美國房地産研究所(RERI)聯合研究課題“城市信息學應用于建築改造與能源效率投資分析”，2018-2021（項目骨幹2/10）
6. 美國彭博資訊科技原型設計研發項目“增強現實數據界面在未來辦公空間應用”，2017-2017（負責人）
【榮譽及獲獎】
2024，第十二屆高校GIS論壇 高校GIS新銳獎
2023，第七屆“城垣杯”規劃決策支持模型設計大賽 優秀獎（指導教師）
2021，首屆全國大學生國土空間規劃設計競賽 二等獎（指導教師）
2021，首屆全國大學生國土空間規劃設計競賽 最佳立意獎（指導教師）
2019，谷歌人工智能社會影響挑戰優勝團隊
2018，聯合國大數據應對氣候變化行動挑戰最佳數據可視化獎
2017，彭博資訊Bloomberg Data for Good Exchange數據科學家獎
2017，美國城市設計論壇前沿學者
2017，彭博資訊與紐約多媒體實驗室（NYC Media Lab）增強現實技術研發學者
2016，紐約大學校園數據信息開發競賽優勝團隊
2015，紐約大學學術獎學金
2014，麻省理工學院醫療信息與數據分析競賽第二名
2011，紐約州立大學布法羅分校建築與城市規劃學院，最佳畢業論文
2011，美國規劃師協會（APA）紐約州分會優秀學生項目獎
【部分學術出版】
期刊論文
1. ZHOU L, LAI Y. Urban Spatial Heat Resilience Indicator Based on Running Activity Z-score[J].Urban Science,2025,9,34.
2. 夏靜怡，莊博凱，來源. 未來城市智能技術促進多領域協同效益研究[J].城市與區域規劃研究，2024，16(1):15-29.
3. SSEBYALA SN, KINTU TM, MUGANZI DJ, DRESSER C, DEMETRES MR, LAI Y, et al. Use of machine learning tools to predict health risks from climate-sensitive extreme weather events: A scoping review[J].PLOS Clim 3(1): e0000338.
4. XIA J, WANG J, LAI Y. Development Strategy Based on Combination Typologies of Building Carbon Emissions and Urban Vibrancy—A Multi-Sourced Data-Driven Approach in Beijing, China[J].Land 2024,13,1062.
5. 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.
6. CHUANG P, LAI Y. Data-driven insights into age-friendly smart community development in China: A case study of Beijing[J].Journal of Chinese Architecture and Urbanism,2024,6(3):1754.
7. 來源, 鄭筱津, 夏靜怡. 城市系統視角的智慧人居理論與技術規劃原則[J].城市規劃, 2023,47(12):89-96.
8. 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.
9. 來源, 胡安妮. 基于人居活動數據的城市分析——紐約市實踐經驗及其城市人因工程學啟示[J].世界建築, 2023, 7(397): 10-16.
10. 來源, 李佳彤.基于居民活動的多尺度城市健康數據融合分析[J].西部人居環境學刊, 2023, 38(2): 8-16.
11. 來源，莊博凱.人民城市理念下的智慧城市規劃價值導向思考[J].北京規劃建設, 2023, 209: 20-25.
12. 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.
13. 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.
14. 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.
15. LAI Y. Urban Intelligence for Carbon Neutral Cities: Creating Synergy among Data, Analytics, and Climate Actions[J]. Sustainability, 2022, 14(12).
16. LAI Y. Urban Intelligence for Planetary Health[J]. Earth, 2021, 2(4): 972-9.
17. 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.
18. 來源, 王钰, 林添怿. 面向綠色基礎設施的城市信息學:紐約市行道樹數據收集、分析與公衆科學的綜合研究[J]. 風景園林, 2021, 28(1): 17-30.
19. 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.
20. LUO E M, NEWMAN S, AMAT M, et al. MIT COVID-19 Datathon: data without boundaries [J]. BMJ Innov., 2021, 7(1): 231-4.
21. LAI Y, YEUNG W, CELI L A. Urban Intelligence for Pandemic Response: Viewpoint [J]. JMIR Public Health Surveill., 2020, 6(2): e18873.
22. 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.
23. 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.
24. 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.
25. 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.
26. 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.
學術著作
1. 來源. 城市信息與數據科學導論：智慧城市系統構造與應用 [M]. 北京: 中國建築工業出版社, 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.
會議論文
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.
項目報告
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.
特邀報告與媒體報道
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.
