助理教授/特別研究員，博士生導(dǎo)師
E-mail：yuanlai@tsinghua.edu.cn
【研究和教學(xué)方向】
城市科學(xué)、城市信息學(xué)、城市設(shè)計、智慧城市、城市健康
【教育經(jīng)歷】
2016-2019，美國紐約大學(xué)土木與城市工程系，工學(xué)博士（城市系統(tǒng)與信息學(xué)方向）
2015-2016，美國紐約大學(xué)城市科學(xué)與發(fā)展中心，理學(xué)碩士（應(yīng)用城市科學(xué)與信息學(xué)專業(yè)）
2009-2011，美國紐約州立大學(xué)布法羅分校，城市規(guī)劃學(xué)碩士 （城市設(shè)計與地理信息系統(tǒng)方向）
2005-2009，北京林業(yè)大學(xué)，風(fēng)景園林學(xué)士
【專業(yè)履歷】
2021.6-至今， 清華大學(xué)建筑學(xué)院城市規(guī)劃系，助理教授/特別研究員，博士生導(dǎo)師
2019.8-2021.5，美國麻省理工學(xué)院城市研究與規(guī)劃系(MIT DUSP)，講師 (城市科學(xué)方向)
2018.9-2019.5，美國紐約大學(xué)城市管理研究所 (NYU Marron Institute)，研究助理
2016.7-2018.7，美國紐約大學(xué)城市科學(xué)與發(fā)展中心 (NYU CUSP)，研究助理
2011.7-2015.8，美國薩夫迪建筑設(shè)計事務(wù)所（波士頓），城市設(shè)計師
【講授課程】
本科生課程：城市設(shè)計；城鄉(xiāng)規(guī)劃基礎(chǔ)（8）
研究生課程：城市信息學(xué)I-城市應(yīng)用分析；城市信息學(xué)II-智慧城市導(dǎo)論
【學(xué)術(shù)兼職】
自然資源部 智慧人居環(huán)境與空間規(guī)劃治理技術(shù)創(chuàng)新中心 技術(shù)帶頭人、副秘書長
中國城市科學(xué)研究會 數(shù)字孿生與未來城市專委會，委員
中國城市規(guī)劃學(xué)會 規(guī)劃實施分會，青年委員
美國城市設(shè)計論壇 (Urban Design Forum) 委員會成員
紐約大學(xué)城市管理研究所研究學(xué)者
國際電氣電機工程師協(xié)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(xué)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(zé)人）
2. 國家重點研發(fā)計劃課題子任務(wù)“多源數(shù)據(jù)高精度融合技術(shù)研究”，2022-2025 （負責(zé)人）
3. 北京卓越青年科學(xué)家計劃“北京城鄉(xiāng)土地利用優(yōu)化的理論、規(guī)劃方法和技術(shù)體系研究”開放課題“基于多源數(shù)據(jù)的北京房地產(chǎn)資源分布與社區(qū)活力分析”，2021-2022（負責(zé)人）
4. 美國國家科學(xué)基金項目“智能和可持續(xù)城市的城市信息學(xué)以及數(shù)據(jù)驅(qū)動的理論研究”，2017-2019（項目骨干2/10）
5. 美國勞倫斯-伯克利國家實驗室(LBNL)與美國房地產(chǎn)研究所(RERI)聯(lián)合研究課題“城市信息學(xué)應(yīng)用于建筑改造與能源效率投資分析”，2018-2021（項目骨干2/10）
6. 美國彭博資訊科技原型設(shè)計研發(fā)項目“增強現(xiàn)實數(shù)據(jù)界面在未來辦公空間應(yīng)用”，2017-2017（負責(zé)人）
【榮譽及獲獎】
2023，第七屆“城垣杯”規(guī)劃決策支持模型設(shè)計大賽 優(yōu)秀獎（指導(dǎo)教師）
2021，首屆全國大學(xué)生國土空間規(guī)劃設(shè)計競賽 二等獎（指導(dǎo)教師）
2021，首屆全國大學(xué)生國土空間規(guī)劃設(shè)計競賽 最佳立意獎（指導(dǎo)教師）
2019，谷歌人工智能社會影響挑戰(zhàn)優(yōu)勝團隊
2018，聯(lián)合國大數(shù)據(jù)應(yīng)對氣候變化行動挑戰(zhàn)最佳數(shù)據(jù)可視化獎
2017，彭博資訊Bloomberg Data for Good Exchange數(shù)據(jù)科學(xué)家獎
2017，美國城市設(shè)計論壇前沿學(xué)者
2017，彭博資訊與紐約多媒體實驗室（NYC Media Lab）增強現(xiàn)實技術(shù)研發(fā)學(xué)者
2016，紐約大學(xué)校園數(shù)據(jù)信息開發(fā)競賽優(yōu)勝團隊
2015，紐約大學(xué)學(xué)術(shù)獎學(xué)金
2014，麻省理工學(xué)院醫(yī)療信息與數(shù)據(jù)分析競賽第二名
2011，紐約州立大學(xué)布法羅分校建筑與城市規(guī)劃學(xué)院，最佳畢業(yè)論文
2011，美國規(guī)劃師協(xié)會（APA）紐約州分會優(yōu)秀學(xué)生項目獎
【部分學(xué)術(shù)出版】
期刊論文
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. 來源, 鄭筱津, 夏靜怡. 城市系統(tǒng)視角的智慧人居理論與技術(shù)規(guī)劃原則[J].城市規(guī)劃, 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. 來源, 胡安妮. 基于人居活動數(shù)據(jù)的城市分析——紐約市實踐經(jīng)驗及其城市人因工程學(xué)啟示[J].世界建筑, 2023, 7(397): 10-16.
5. 來源, 李佳彤.基于居民活動的多尺度城市健康數(shù)據(jù)融合分析[J].西部人居環(huán)境學(xué)刊, 2023, 38(2): 8-16.
6. 來源，莊博凱.人民城市理念下的智慧城市規(guī)劃價值導(dǎo)向思考[J].北京規(guī)劃建設(shè), 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. 來源, 王鈺, 林添懌. 面向綠色基礎(chǔ)設(shè)施的城市信息學(xué):紐約市行道樹數(shù)據(jù)收集、分析與公眾科學(xué)的綜合研究[J]. 風(fēng)景園林, 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.
學(xué)術(shù)著作
1. 來源. 城市信息與數(shù)據(jù)科學(xué)導(dǎo)論：智慧城市系統(tǒng)構(gòu)造與應(yīng)用 [M]. 北京: 中國建筑工業(yè)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.
