个人简介（下载简历）

吕欣，博士，国防科技大学系统工程学院教授。国际非营利组织Flowminder基金会创始人、理事、首席分析师。

主要研究方向为大数据挖掘；复杂网络；统计抽样；应急管理；公共卫生。长期围绕大数据挖掘、复杂网络算法的核心技术及人类行为分析的研究主题，面向解决“贫穷、疾病、灾害”的数据模型开展理论探索和前沿应用。通过将大数据技术应用于灾害条件下大规模人类行为规律挖掘和模式提取，其研究促进了国际组织自然灾害救援方式的转变，在海地地震与霍乱疫情、日本3·11大地震与海啸、孟加拉Mahasen台风、西非国家埃博拉疫情、中国登革热疫情、尼泊尔地震与洪水、新冠肺炎疫情等重大灾害事件的应急救援管理实践中得到广泛应用。

World Economic Forum: "The example from Haiti demonstrates how mobile data analysis could revolutionize disaster and emergency responses."
                  —《Big Data, Big Impact: New Possibilities for International Development》, pg. 5

研究成果发表在Nature、Nature Communications、Nature Microbiology、PNAS、National Science Review、The Innovation、Physics Reports、PLOS Medicine、International Journal of Epidemiology、Journal of the Royal Statistical Society: Series A、Social Networks、Global Environmental Change、Omega等高水平期刊上，多次得到顶级期刊专文进行评价和前景讨论（PLOS Medicine, 2011;PNAS, 2012;PNAS, 2016)。

研究多次得到BBC (2011, 2014, 2015, 2020)、New York Times (2011, 2020)、MIT (2013, 2014)、Scientific American (2019)、Science Daily (2017, 2018, 2019, 2020)、联合国人道主义事务协调厅（UNOCHA, 2015）、世界经济论坛（WEF, 2012）等的高度评价。 得到人民日报、外交部、国防部、新华社、国家自然科学基金委、科技日报、解放军报等高度评价。诺贝尔医学和生理学奖颁布单位卡罗林斯卡学院两次将其两项研究在主页上作新闻发布。技术方法被MIT Technology Review列为“全球十大突破性技术”。获世界移动大会最佳应用奖（GLOMO Award），国家级教学成果二等奖，湖南省青年科技奖，湖南省高等教育教学成果特等奖，教育部科技进步二等奖，中国仿真学会自然科学一等奖，全国复杂网络大会可视化一等奖，军队科技进步二等奖。

代表作

• Jia J, Lu X, et al., Population flow drives spatio-temporal distribution of COVID-19 in China. Nature. 2020. 582(7812): 389-394. (pdf)
  
• Buckee CO, Tatem AJ, Wetter E, Lu X & Bengtsson L, Society: Protect privacy of mobile data. Nature, 2014. 514(7520): p. 35-35. (correspondence, pdf)
• Zhang J, et al., Heterogeneous changes in mobility in response to the SARS-CoV-2 Omicron BA.2 outbreak in Shanghai. Proceedings of the National Academy of Sciences, 2023. 120(42): p. e2306710120. (pdf)
  
• Lu X, Bengtsson L, & Holme P, Predictability of population displacement after the 2010 Haiti earthquake. Proceedings of the National Academy of Sciences, 2012. 109(29): p. 11576-11581. (pdf)
  
• Zhang, Z-K, et al., Dynamics of information diffusion and its applications on complex networks. Physics Reports, 2016. 651: p. 1-34. (pdf)
  
• Kraemer M, et al., Past and future spread of the arbovirus vectors Aedes aegypti and Aedes albopictus. Nature Microbiology, 2019. 3: p. 1-10. (pdf)
  
• Zhou B, et al., The nature and nurture of network evolution. Nature Communications, 2023. 14(1): p. 7031. (pdf)
  
• Jia J, Li Y, Lu X, et al., Triadic embeddedness structure in family networks predicts mobile communication response to a sudden natural disaster. Nature Communications, 2021. 12(1): p. 4286. (pdf)
  
• Zhao Y, et al., Towards parallel intelligence: An interdisciplinary solution for complex systems. The Innovation, 2023. 4(6): p. 100521. (pdf)
  
• Zhu Z, et al., Strategy evaluation and optimization with an artificial society toward a Pareto optimum. The Innovation, 2022. 3(5): p. 1-3. (pdf)
  
• Tan S, et al., Mobility in China, 2020: a tale of four phases. National Science Review, 2021. 8(11): p. nwab148. (pdf)
  
• Lu X, et al., Unveiling hidden migration and mobility patterns in climate stressed regions: A longitudinal study of six million anonymous mobile phone users in Bangladesh. Global Environmental Change, 2016,38:1-7. (pdf)
• Lu X, et al., Mobile Phone-Based Population Flow Data for the COVID-19 Outbreak in Mainland China. Health Data Science, 2021. p. 9796431. (pdf)
  
• Zhou B, Lu X, and Holme P, Universal evolution patterns of degree assortativity in social networks. Social Networks. 2020. 63: p. 47-55. (pdf)
  
• Lu X, Linked Ego Networks: Improving estimate reliability and validity with respondent-driven sampling. Social Networks, 2013. 35(4): p. 669-685. (pdf)
  
• Lu X, A.L. Horn, J. Su, and J. Jiang, A Universal Measure for Network Traceability. Omega, 2019. 87: p. 191-204. (pdf)
  
• Lu X, et al., Detecting climate adaptation with mobile network data in Bangladesh: anomalies in communication, mobility and consumption patterns during cyclone Mahasen. Climatic Change, 2016. 138(3): p. 505-519. (pdf)
  
• Lu X, et al., Approaching the limit of predictability in human mobility. Scientific Reports, 2013. 3. (pdf)
  
• Lu X, et al., The sensitivity of respondent-driven sampling. Journal of the Royal Statistical Society: Series A (Statistics in Society), 2012. 175(1): p. 191-216. (pdf)
  
• Bengtsson L, Lu X, Thorson A, Garfield R, Schreeb J, Improved Response to Disasters and Outbreaks by Tracking Population Movements with Mobile Phone Network Data: A Post-Earthquake Geospatial Study in Haiti. PLoS Medicine, 2011. 8(8): p. e1001083. (pdf)