刘博  

1.基本情况:

教育背景:

2003年于北京理工大学自动化系获学士学位

2008年于清华大学自动化系获博士学位


任职情况:

2008年至2010年在NEC中国研究院担任副研究员

2011年至2012年在美国芝加哥大学及Argonne国家实验室担任Research Professional

2013年至2015年在NEC中国研究院担任研究员

2015年至今在北京工业大学软件学院任副教授

现任信息学部软件学院副院长、软件工程专业负责人

博士生导师

2. 主要研究方向:

大数据,数据挖掘,机器学习,云计算,企业建模及工作流,语义网及本体推理

3. 研究成果与奖励:

曾参与十余个研究项目,包括国家863项目、自然科学基金项目、欧盟第六框架FP6项目、与IBM中国研究院的合作项目、与金蝶公司、东软公司的合作项目等。2011-2012年在美国芝加哥大学及Argonne国家实验室工作期间,参与了多个国家级项目,包括美国国家卫生研究院(NationalInstitutes of HealthNIH)支持的“癌症生物医学信息网格”,美国国家心脏、肺和血液研究所(NHLBI)支持的“心血管研究网格”等,对于如何将云计算、工作流用于医学大数据分析积累了丰富的研究经验。在NEC中国研究院工作期间,专注于时空数据的挖掘与分析,并将数据挖掘和语义分析的技术应用于医疗健康和大气污染领域。

目前主持国家自然科学基金、北京市自然科学基金、北京市教委科技计划等多个项目,重点关注气象及医疗领域的大数据分析。至今在国内国际会议及期刊发表论文近50篇,有40余项技术发明在中国及日本提交了专利申请,已获中国专利授权10项及日本专利授权7项,软件著作权4项。作为IEEE SeniorMember以及多个国际会议及期刊的审稿人,在研究领域内具有一定的影响力。

4.    发表的部分学术论文:

  1. Liu B, Yan S, You HL, Dong Y, Li Y, Lang JL, Gu RT. RoadSurface Temperature Prediction based on Gradient Extreme Learning Machine Boosting.Computers in Industry, Apr. 2018, pp.294–302. (IF:2.731)

  2. Liu B, Yan S, You HL, Dong Y, Li JQ, Li Y, Lang JL,Gu RT. An Ensembled RBF Extreme Learning Machine to Forecast Road SurfaceTemperature. The 16th IEEE International Conference on Machine Learning andApplications (IEEE ICMLA'17), Cancun, Mexico. Dec. 18-21, 2017. (EI)

  3. Liu B, Liu YX, Li JQ, Lang JL, Gu RT.Multi-Dimensional Motif Discovery in Air Pollution Data. IEEE SMC 2017, Banff,Canada. Oct. 5-8, 2017. (EI)

  4. Liu B, Yao KL, Wei L, Fei XL, Wang Q. Theinvestigation on effectiveness evaluation methods for one medical material usedfor surgery patients based on Electronic Medical Records data. COMPSAC 2017.Torino, Italy. Jul. 4-8, 2017. (EI)

  5. Liu B, Yan S, Li JQ, Li Y. Forecasting PM2.5Concentration using Spatio-Temporal Extreme Learning Machine. The 15th IEEEInternational Conference on Machine Learning and Applications (IEEE ICMLA'16),Anaheim, California, USA. Dec. 18-20, 2016, pp.950-953. (EI)

  6. Liu B, Li JQ, Yang JJ, Bi J, Li R, Li Y. PatternRecognition for Large-scale and Incremental Time Series in Healthcare. COMPSAC2016. Atlanta, USA. Jun. 10-14, 2016, pp.653-658. (EI)

  7. Liu B, Li JQ, Chen C, Tan W, Chen Q, Zhou MC.Efficient Motif Discovery for Large-scale Time Series in Healthcare. IEEE Transactions on Industrial Informatics.Vol. 11, Issue 3, Jun. 2015, pp.583-590. (IF:8.785)

  8. Liu B, Huang KM, Li JQ, Zhou MC. An Incremental andDistributed Inference Method for Large-scale Ontologies based on MapReduceParadigm. IEEE Transactions on Systems,Man, and Cybernetics, Part B: Cybernetics. Vol. 45, No. 1, Jan. 2015, pp.53-64.(IF: 3.236)

  9. Liu B, Wu L, Dong QX, Zhou YC. Large-scaleHeterogeneous Program Retrieval through Frequent Pattern Discovery and FeatureCorrelation Analysis. IEEE 2014International Congress on Big Data, Jun. 27-Jul. 2, 2014, Anchorage,Alaska, USA, pp.780-781.

  10. Liu B, Wu L, Li JQ, Yang JJ. Exploiting IncrementalReasoning in Healthcare based on Hadoop and Amazon Cloud. Workshops at the Twenty-Eighth AAAI Conference on ArtificialIntelligence. Québec City, Canada, Jul. 27-31, 2014, pp.16-22.

  11. Liu B, Madduri R, Sotomayor B, Chard K, Lacinski L,Dave U, Li JQ, Liu CC, Foster I. Cloud-based Bioinformatics Workflow Platformfor Large-scale Next-generation Sequencing Analyses. Journal of Biomedical Informatics. Vol. 49, 2014, pp.119-133. (IF: 2.434)

  12. Liu B, Sotomayor B, Madduri R, Chard K, Foster I.Deploying Bioinformatics Workflows on Clouds with Galaxy and Globus Provision. Supercomputing. Salt Lake City, USA.Nov. 10-16, 2012, pp. 1087-1095.

  13. Liu B, Li JQ, Zhao Y. Repairing and Reasoning withInconsistent and Uncertain Ontologies. Advancesin Engineering Software, Vol.45 (1), 2012, pp. 380-390. (IF: 1.092)

  14. Liu B, Fan YS, Huang SX. A Service-Oriented BusinessPerformance Evaluation Model and Performance-Aware Service Selection Method. Concurrency and Computation: Practice andExperience. Vol. 20(15), 2008, pp.1821-1836. (IF:1.791)

  15. Wu L, Du L, Liu B, Xu GD, Ge Y, Fu YJ, Li JH, ZhouYC, Xiong H. Heterogeneous Metric Learning with Content-based Regularizationfor Software Artifact Retrieval. IEEEInternational Conference on Data Mining (ICDM 2014). Shen Zhen, China,Dec.14-17, 2014, pp.610-619.

  16. Madduri R, Sulakhe D, Lacinski L, Liu B, RodriguezA, Chard K, Dave U, Lacinski L, Foster I. Experiences Building GlobusGenomics:A Next-Generation Sequencing Analysis Service using Galaxy, Globus,and Amazon Web Services. Concurrency andComputation: Practice and Experience. Vol. 26, Issue. 13, Sep. 2014, pp.2266-2279. (IF: 0.845)

  17. Li JQ, Yang JJ, Liu CC, Zhao Y, Liu B, Shi YL.Exploiting Semantic Linkages among Multiple Sources for Semantic InformationRetrieval. Enterprise Information Systems,Vol. 8(4), 2014, pp.464-489. (IF: 9.256)

  18. Li JQ, Liu CC, Liu B, Mao R, Wang YC, Chen S, YangJJ, Pan H, Wang Q. Diversity-aware Retrieval of Medical Records. Computers in Industry. Oct. 2014. (IF: 2.028)

5.    联系方式:

       电话:010-67396762邮箱:boliu@bjut.edu.cn


北京工业大学研究生招生办公室 地址:北京市朝阳区平乐园100号 邮政编码:100124 联系电话:010-67392533