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People

Name:
Li Jianhui
Gender:
Title:
Research Scientist & Professor
Post:
Director of Science and Technology Cloud Department
Dept:
Tel:
86-10-58812518
E-Mail:
lijh@cnic.cn
Edu:
  • Resume:
  • Li Jianhui is the department director of CNIC, and Professor and PhD Supervisor at the University of Chinese Academy of Sciences. He had worked on data infrastructure, data management and data-intensive computing since 1999, and currently serves as the Director of Science and Technology Cloud Department, which is responsible for the operation of China Science and Technlogy Cloud.

  • Research Direction:
  • Big Data and cloud computing, open data and open science, digital research infrastructure, AIOPS

  • Projects Undertook:
  • 2021-2023, CAS Program for Fostering International Mega-science: Global Open Science Cloud Initiative, (No. 241711KYSB20200023), PI.
    2021-2024, The National Key Research and Development Program, “China-Europe Cross- continental Open Science Cloud Federation Technology and Demonstration” (No. 2021YFE0111500), PI.

    2021-2025 , CAS 14th Five-year Informationization Plan Program, “China S&T Cloud Engineering” (CAS-WX2022GC-01), PI

    2018-2022, CAS Strategic Pioneer Research and Development Program “Big Earth Data Science Engineering (No. XDA19000000, CASEarth)”, key technical expert and PI for sub- program No. XDA19020100.

    2016-2019, The National Key Research and Development Program, “Scientific Big Data Management System” (No.2016YFB1000600), PI.

    2017-2020, The Chinese Academy of Sciences Informatization Program, “Big Scientific Data Engineering”, PI.

    2013-2015, National Science Foundation of China, “Cloud Service and Key Technology for Emergency Management” (No. 91224006), PI.

    2013-2015, National Development and Reform Commission, “Big Data Analysis and Service Platform for Basic Research”, PI.

    2012-2018, Chinese Academy of Sciences Informatization Program, “Research Data Integration and Sharing”, PI.

    2009-2012, Ministry of Science and Technology, National Science and Technology Infrastructure, “National Data Sharing Network for Basic Research”, CO-PI.

  • Social Service:
  • Vice President of the Committee on Data of International Science Council, Vice President of the Chinese National Committee for International Science Council
  • Publication:
  • [1]. LI Jianhui, Wu, C., Piao, Y. et al. (2023). How can we support the UN Sustainable Development Goals when open data is stagnant? Science Bulletin. https://doi.org/10.1016/j.scib.2023.05.021 

    [2]. Zhang, L., LI Jianhui, Paul F. U. et al. (2023). Research e-infrastructures for open science: The national example of CSTCloud in China. Data Intelligence 2023; 5 (2): 355–369. https://doi.org/10.1162/dint_a_00196 

    [3].Zhou X., Yang, K., Jiang, Y., Sun, J., Chen, Y., Li, X., LI Jianhui et al. (2022). The Influence of Bare Ground Thermal Roughness Length Parameterization on the Simulation of Near ‐ Surface Air and Skin Temperatures Over the Tibetan Plateau. Journal of Geophysical Research. Atmospheres, 127(21). https://doi.org/10.1029/2022JD037245 

    [4]. Li, Zhou, Y., Zheng, X., Zhang, Z., Jiang, L., Li, Z., Wang, P., LI Jianhui, et al. (2022). Tracing the footsteps of open research data in China. Learned Publishing, 35(1), 46–55. https://doi.org/10.1002/leap.1439 

    [5]. Liao, F. & LI Jianhui. (Eds.). (2021). Open Science Cloud Technology and Practice. China Science Publishing & Media Ltd. pp. 1-349 (In Chinese)

     

    [6]. Zhang L., Downs, R. R., LI Jianhui et al. (2021). A Review of Open Research Data Policies and Practices in China. Data Science Journal, 20(1). https://doi.org/10.5334/dsj- 2021-003 

    [7].Wen, L., Zhang, L., Li, Y., & LI Jianhui. (2021). AVEI: A Scientific Data Sharing Framework Based on Blockchain. In Intelligent Computing and Block Chain. FICC 2020. Communications in Computer and Information Science, vol 1385. Springer, Singapore. https://doi.org/10.1007/978-981-16-1160-5_21 

    [8]. Chen, Y., LI Jianhui, Hodson, S. et al. (2021). The Global Open Science Cloud Landscape. EGI Conference 2020, Virtual. https://doi.org/10.5281/zenodo.5575275 

    [9]. Guo, H., Nativi, S., Liang, D., Craglia, M., Wang, L., Schade, S., Corban, C., He, G., Pesaresi, M., LI Jianhui et al. (2020). Big Earth Data science: an information framework for a sustainable planet. International Journal of Digital Earth, 13(7), 743–767. https://doi.org/10.1080/17538947.2020.1743785 

    [10]. LI Jianhui, Meng, X., Zhang, Y. et al. (2019). Big Scientific Data Management First Int ernational Conference, BigSDM 2018, Beijing, China. Lecture notes in Computer Science, 11473. pp1-332.

    [11].Wang, H., LI Jianhui et al. (2018). Approximations and bounds for ( n , k ) fork-join queues: a linear transformation approach. 2018 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID), 422–431. https://doi.org/10.1109/CCGRID.2018.00069 

    [12]. LI Jianhui, Li, Y., Wang, H., & Chen, M. (2018) Scientific Big Data Management Technique and System, Bulletin of Chinese Academy of Sciences: Vol. 33: Iss. 8, Article 5. DOI: https://doi.org/10.16418/j.issn.1000-3045.2018.08.005 Available at: https://bulletinofcas.researchcommons.org/journal/vol33/iss8/5 (In Chinese)

    [13]. Wang P., Liu, G., Fu, Y., Zhou, Y., & LI Jianhui. (2018). Spotting Trip Purposes from Taxi Trajectories: A General Probabilistic Model. ACM Transactions on Intelligent Systems and Technology, 9(3), 1–26. https://doi.org/10.1145/3078849 

    [14]. LI Jianhui, Shen, Z., & Meng, X. (2017). Scientific Big Data Management: Concepts, Technologies and System. Journal of Computer Research and Development, 54.02, pp.235-247. DOI:10.7544/issn1000-1239.2017.20160847 (In Chinese)

    [15]. Cui, W., Du Y., Shen, Z., & LI Jianhui (2017). Personalized microblog recommendation using sentimental features, 2017 IEEE International Conference on Big Data and Smart Computing (BigComp), Jeju, Korea (South), 2017, pp. 455-456, doi: 10.1109/BIGCOMP.2017.7881756.

    [16]. Cui, W., Wang, P., Du, Y., Chen, X., Guo, D., LI Jianhui, & Zhou, Y. (2017). An algorithm for event detection based on social  media  data. Neurocomputing (Amsterdam), 254, 53–58. https://doi.org/10.1016/j.neucom.2016.09.127 

    [17]. Du, Y., Ma, C., Wu, C., Xu, X., Guo, Y., Zhou, Y., & LI Jianhui. (2017). A Visual Analytics Approach for Station-Based Air Quality Data. Sensors (Basel, Switzerland), 17(1), 30–30. https://doi.org/10.3390/s17010030 

     

    [18]. LI Jianhui, Zhou, Y., Hu, L. et al. (2016). Scientific data cloud construction and service of Chinese Academy of Sciences. Big Data Research, 02.06, pp.3-13. DOI:10.11959/j.issn.2096-0271.2016061. (In Chinese)

    [19]. Meng, Z., Dong, H., LI Jianhui et al. (2015). Darwintree: A Molecular Data Analysis and Application Environment for Phylogenetic Study. Data Science Journal, 14, 10. https://doi.org/10.5334/dsj-2015-010 

    [20].Wang H., LI Jianhui et al. (2014). Benchmarking Replication and Consistency Strategies in Cloud Serving Databases: HBase and Cassandra. In Big Data Benchmarks, Performance Optimization, and Emerging Hardware (pp. 71–82). Springer International Publishing. https://doi.org/10.1007/978-3-319-13021-7_6 

    [21]. Xue, Z., Shen, G., LI Jianhui et al. (2012). Compression-aware I/O performance analysis for big data clustering. Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining, 45–52.https://doi.org/10.1145/2351316.2351323 

    [22]. Xiao X., LI Jianhui et al. (2012). Framework for phenology analyses from observation data of digital images and meteorological data. 2012 IEEE International Conference on Computer Science and Automation Engineering (CSAE), 2, 373–377. https://doi.org/10.1109/CSAE.2012.6272795 

    [23]. Meng, Z., LI Jianhui et al. (2011). bCloudBLAST: An efficient mapreduce program for bioinformatics applications. 2011 4th International Conference on Biomedical Engineering and Informatics (BMEI), 4, 2072–2076. https://doi.org/10.1109/BMEI.2011.6098717 

    [24].Tang, M., Zhou, Y., Li, J., Wang, W., Cui, P., Hou, Y., Luo, Z., LI Jianhui et al. (2011). Exploring the wild birds’ migration data for the disease spread study of H5N1: a clustering and association approach. Knowledge and Information Systems, 27(2), 227–251. https://doi.org/10.1007/s10115-010-0308-x