个人简历

1991年7月-1993年7月，武汉测绘科技大学航测与遥感系/测绘遥感信息工程国家重点实验室 助教
1999年8月-2001年3月，中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室博士后
2001年4月-2004年6月 中国科学院地理科学与资源研究所副研究员
2004年4月-2004年12月 香港大学高级访问学者
2004年6月-中国科学院地理科学与资源研究所研究员
2008年9月-中国科学院地理科学与资源研究所博士生导师
2001年4月-历任中国科学院地理科学与资源研究所资源与环境信息系统国家重点实验室副主任、国家遥感中心地理信息系统部主任、资源与环境信息系统国家重点实验室常务副主任、中国科学院地理科学与资源研究所所长助理、所学术委员会委员、党委委员、纪委委员

研究领域

地理空间大数据管理、移动对象数据库技术、文本挖掘与知识图谱、移动对象轨迹数据挖掘、地理空间大数据机器学习模型与算法、复杂网络分析、导航与位置服务技术、交通地理信息系统等

近期论文

Xiliang Liu, Feng Lu, T-CRF: A novel map matching approach for low-frequency floating car data, ACM SIGSpatial Conference, Nov. 03, 2015, Seattle, U.S.
Zhang Jianqin, Qiu Peiyuan, Duan Yingchao, Du Mingyi, Lu Feng, A space-time visualization analysis method for taxi operation in Beijing, Journal of Visual Languages and Computing, 31(2015), 1-8
Ziliang Zhao, Shih-Lung Shaw, Yang Xu, Feng Lu, Jie Chen, Ling Yin, Understanding the bias of call detail records in human mobility research, International Journal of Geographical Information Science, 2016, 30(9):1738-1762
Yang Xu, Shih-Lung Shaw, Ziliang Zhao, Ling Yin, Feng Lu, Jie Chen, Zhixiang, Fang & Qingquan Li. Another tale of two cities: understanding human activity space using actively tracked cellphone location data, Annals of the Association of American Geographers, 2016, 106(2): 489-502.
Kang Liu, Peiyuan Qiu, Mingxiao Li, Xiliang Liu, Feng Lu, Exploring urban travel routes’ characteristics from a geometric perspective, GeoInformatics’2016, doi: 10.1109/GEOINFORMATICS.2016.7578981
Xiliang Liu, Li Yu, Peng Peng, Feng Lu*, A stacked generalization framework for city traffic related geospatial data analysis, APWeb/SDMA 2016, In: Morishima A. et al. (eds) Web Technologies and Applications. APWeb 2016. Lecture Notes in Computer Science, vol 9865. Springer, Cham
Xiliang Liu, Feng Lu, Kang Liu, Peiyuan Qiu, Li Yu, Mingxiao Li, A Principal curve-based method for geospatial data smoothing, GIScience 2016
Xiliang Liu, Kang Liu, Mingxiao Li, Feng Lu*, A ST-CRF map-matching method for low-frequency floating car data, IEEE Transactions on Intelligent Transportation Systems, 2017, 18(5):1241-1254
Shifen Cheng, Feng Lu*, A Two-step method for missing spatio-temporal data reconstruction, ISPRS International Journal of Geo-Information, 2017, 6, 187; doi:10.3390/ijgi6070187
Xiliang Liu, Li Yu, Kang Liu, Peng Peng, Shifen Cheng, Mengdi Liao, and Feng Lu*, 2017, ST-PF: Spatio-temporal particle filter for floating car data pre-processing, V. Popovich et al. (eds.), Information Fusion and Intelligent Geographic Information Systems (IF&IGIS’17), Lecture Notes in Geoinformation and Cartography, DOI 10.1007/978-3-319-59539-9_15
Kang Liu, Song Gao, Peiyuan Qiu, Xiliang Liu, Bo Yan, Feng Lu*, Road2Vec: measuring traffic interactions in urban road system from massive travel routes, ISPRS International Journal of Geo-Information, 2017, 6, 321; doi:10.3390/ijgi6110321
Yang Xu, Shi-lunh Shaw*, Feng Lu, Jie Chen, Qingquan Li, Uncovering the relationships between phone communication activities and spatiotemporal distribution of mobile phone users, in Shaw S.L. and Sui D. (eds.), Human Dynamics Research in Smart and Connected Communities, Springer International Publishing AG, 2018, DOI: 10.1007/ 978-3-319-73247-3_3
Feng Lu, Kang Liu, Yingying Duan, Shifen Cheng, Fei Du, Modelling the heterogeneous traffic correlation for city road networks with community detection, Physica A, 2018, doi.org/10.1016/j.physa.2018.02.062
Jie Chen, Tao Pei, Shih-Lung Shaw, Feng Lu, Mingxiao Li, Shifen Cheng, Xiliang Liu & Hengcai Zhang, Fine-grained prediction of urban population using mobile phone location data, International Journal of Geographical Information Science, 2018, DOI: 10.1080 /13658816.2018.1460753
Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu, Short-term traffic forecasting: an adaptive ST-KNN model that considers spatial heterogeneity, Computers, Environment and Urban Systems, 2018, 71:186-198
Shifen Cheng, Feng Lu*, Short-Term Traffic Forecasting: A dynamic ST-KNN model considering spatial heterogeneity and temporal non-stationarity, in Nikolaus Augsten Proceedings of the Workshops of the EDBT/ICDT 2018 Joint Conference (EDBT/ICDT 2018), Vienna, Austria, March 26, 2018. Volume 2083 of CEUR Workshop Proceedings, 133-140
Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu, A spatiotemporal multi-view-based learning method for short-term traffic forecasting, ISPRS International Journal of Geo-Information, 2018, 7(6): 218; doi:10.3390/ijgi7060218
Kang Liu, Song Gao, Feng Lu*, Identifying spatial interaction patterns of vehicle movements on urban road networks by topic modelling, Computers, Environment and Urban Systems, 2019, 74: 50-61
Shifen Cheng, Feng Lu*, Peng Peng, Sheng Wu, Multi-task and multi-view learning based on particle swarm optimization for short-term traffic forecasting, Knowledge-Based Systems, 2019, https://doi.org/10.1016/j.knosys.2019.05.023.