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Gao Ming

  • About

    • Department: School of Data Science and Engineering
    • Gender: male
    • Post:
    • Graduate School: Fudan University
    • Degree: PH. D
    • Academic Credentials:
    • Tel: +86-21-62232061
    • Email: mgao@dase.ecnu.edu.cn
    • Office: Math Building,ECNU
    • Address: Rm. 115, Math Building, No.3663North ZhongshanRd, Shanghai, China, 200062
    • PostCode:
    • Fax:

    WorkExperience

    Education

    Resume

    I am working as a professor of School of Data Science and Engineering (DASE)， East China Normal University. Prior to joining ECNU, I worked with Prof. Ee-Peng Lim as a Postdoctoral Fellow at Social Network Mining Research Group in School of Information System, Singapore Management University. Before that, I started my PhD program in 2008 at Fudan University, Shanghai, China. From Aug. 2010 to Feb. 2011, I also worked as an intern at Database Research Lab 3: Electronic Commerce & Database, School of Computing, National University of Singapore.


    My main research interests are knowledge graph, knowledge engineering, user profiling, social mining (community detection on social networks & understanding topological structure of networks) and uncertain data management.

    Other Appointments

    Conference Review:


    DASFAA 2009, VLDB 2009, ICDE 2010, ICDE 2011, ICDE 2012, SDM 2012, ICDM 2013, ICDE 2013, SDM 2013

     

    Journal Review:


    IEEE Transactionson Knowledge and Data Engineering （TKDE）

    ACM Transactions on Management Information Systems (TMIS)

    Journal of Systems and Software (JSS)

    Social Network Analysis and Mining Journal (SNAM)
    Computer Journal
    Frontiers of Computer Science (FCS)

    Research Fields

    User Profiling and Its Applications; Social Data Management and Mining; Streaming Data Mining and Management; Uncertain Data Management and Mining;

    Enrollment and Training

    Course

    ************************************** 2020 *************************************


    1. Discrete Mathematics and Its Applications, Spring 2020

    Undergraduate level course at School of Data Science and Engineering, East China Normal University


    2. Statistical Inference, Spring 2020

    Graduate level course at School of Data Science and Engineering, East China Normal University


    3. Algorithm Foundations of Data Science, Spring 2020

    Graduate level course at School of Data Science and Engineering, East China Normal University


    ************************************** 2019 *************************************


    1. Discrete Mathematics and Its Applications, Fall 2019

    Undergraduate level course at School of Data Science and Engineering, East China Normal University


    2. Statistical Inference, Spring 2019

    Graduate level course at School of Data Science and Engineering, East China Normal University


    3. Algorithm Foundations of Data Science, Spring 2019

    Graduate level course at School of Data Science and Engineering, East China Normal University


    ************************************** 2018 *************************************


    1. Mathematical Statistics and Data Analysis, Fall 2018

    Undergraduate level course at School of Data Science and Engineering, East China Normal University


    2. Discrete Mathematics and Its Applications, Fall 2018

    Undergraduate level course at School of Data Science and Engineering, East China Normal University


    3. Statistical Inference, Spring 2018

    Graduate level course at School of Data Science and Engineering, East China Normal University


    4. Algorithm Foundations of Data Science, Spring 2018

    Graduate level course at School of Data Science and Engineering, East China Normal University


    ************************************** 2017 *************************************


    1. Discrete Mathematics and Its Applications, Fall 2017

    Undergraduate level course at School of Data Science and Engineering, East China Normal University


    ************************************** 2016 *************************************


    1. Foundation of Data Science, Fall 2016

    Graduate level course at Software Engineering Institute & School of Data Science and Engineering, East China Normal University


    2. Operating System Concepts, Fall 2016

    Undergraduate level course at Software Engineering Institute, East China Normal University


    ************************************** 2015 *************************************


    1. Operating System Concepts, Fall 2015

    Undergraduate level course at Software Engineering Institute, East China Normal University


    2. Operating System Concepts, Spring 2015

    Undergraduate level course at Software Engineering Institute, East China Normal University


    ************************************** 2014 *************************************


    1. Implementation of Database Systems, Fall 2014

    Graduate level course at Software Engineering Institute, East China Normal University


    ************************************** End ************************************** 



    Scientific

    Academic Achievements

    Selected Journal Papers:

    [J18] Ming Gao, Xiangnan He, Leihui Chen, Tingting Liu, Jinglin Zhang, Aoying Zhou. Learning Vertex Representations for Bipartite Networks. TKDE 2020 (CCF-A)

    [J17]Yingnan Fu, Tingting Liu, Ming Gao, Aoying Zhou. EDSL: An Encoder-Decoder Architecture with Symbol-Level Features for Printed Mathematical Expression Recognition. CoRR abs/2007.02517 (2020)

    [J16] Jun Kuang, Yixin Cao, Jianbing Zheng, Xiangnan He, Ming Gao, Aoying Zhou. Improving Neural Relation Extraction with Implicit Mutual Relations. CoRR abs/1907.05333 (2019)

    [J15] Chao Kong, Ming Gao, Chen Xu, Yunbin Fu, Weining Qian, Aoying Zhou. EnAli: Entity Alignment across Multiple Heterogeneous Data Sources. FCS 2019. (SCI)

    [J14] Jihong Yan, Chen Xu, Na Li, Ming Gao, Aoying Zhou. Optimizing model parameter for entity summarization across knowledge graphs. J. Comb. Optim. 37(1): 293-318 (2019) . (SCI)

    [J13] Ming Gao, Xiangnan He, Leihui Chen, Tingting Liu, Jinglin Zhang, Aoying Zhou. Learning Vertex Representations for Bipartite Networks. CoRR abs/1901.09676 (2019)  

    [J12] Jihong Yan, Chengyu Wang, Wenliang Cheng, Ming Gao, Aoying Zhou. A Retrospective of Knowledge Graphs. Frontiers of Computer Science 2018. (SCI)

    [J11] Xiangnan He, Ming Gao, Min-Yen Kan and Dingxian Wang. BiRank: Towards Ranking on Bipartite Graphs. TKDE 2017, 29(1): 57-71. (CCF-A)

    [J10] Xiangnan He, Ming Gao, Min-Yen Kan, Dingxian Wang. BiRank: Towards Ranking on Bipartite Graphs. CoRR abs/1708.04396 (2017)

    [J9] Rong Zhang, Ming Gao, Xiaofeng He, Aoying Zhou. Learning User Credibility for Product Ranking. Knowledge of Information System 2016, 46(3): 679-705. (CCF-B)

    [J8] Xindong Wu, Huanhuan Chen, Gongqing Wu, Jun Liu, Qinghua Zheng, Xiaofeng He, Aoying Zhou, Zhongqiu Zhao, Bifan Wei, Ming Gao, Yang Li, Qiping Zhang, Shichao Zhang, Nanning Zheng. Knowledge Engineering with Big Data. IEEE Intelligent Systems 2015, 30(5): 46-55. (SCI)

    [J7] Jihong Yan, Wenliang Cheng, Chenyu Wang, Jun Liu, Ming Gao, Aoying Zhou. Optimizing Word Set Coverage for Multi-event Summarization. Journal of Combinatorial Optimization 2015. (SCI)

    [J6] Ming Gao, Ee-Peng Lim, David Lo, and Philips Kokoh Prasetyo. On Detecting Maximal Quasi Antagonistic Communities in Signed Graphs. DMKD 2015. (CCF-B)

    [J5] Ming Gao, Cheqing Jin, Weining Qian, and Xueqing Gong. Real-time and Personalized Search over a Microblogging System, The Computer Journal 2013. (SCI)

    [J4] 高明, 金澈清, 钱卫宁, 王晓玲, 周傲英. 面向微博系统的个性化实时推荐, 计算机学报, 2014.  (中文CCF-A，获得2014-2019年优秀论文奖)

    [J3] 高明, 金澈清, 王晓玲, 周傲英. 数据世系管理技术研究综述, 计算机学报, 2010,33(3): 373-389.  (中文CCF-A)

    [J2] 田秀霞, 王晓玲, 高明, 周傲英. 数据库服务-安全与隐私保护, 软件学报, 2010, 21(5).  (中文CCF-A)

    [J1] 许晓峰, 金澈清, 高明, 周傲英. 面向大型数据集合的关键分类查找算法, 计算机研究与发展, 2009, 46(10): 470-476. (中文CCF-A)


    Selected Conference Papers:

    [C27] Na Li, Renyu Zhu, Xiaoxu Zhou, Xiangnan He, Ming Gao, Aoying Zhou. On Disambiguating Authors: Collaboration Network Reconstruction in a Bottom-up Manner. ICDE 2021 (CCF-A)

    [C26] Lisi Ai, Baoli Gao, Jianbing Zheng, Ming Gao. On Improving Text Generation Via Integrating Text Coherence. CCIS 2019: 6-10

    [C25] Jun Kuang, Yixin Cao, Jianbing Zheng, Xiangnan He, Ming Gao, Aoying Zhou. Improving Neural Relation Extraction with Implicit Mutual Relations. ICDE 2020: 1021-1032  (CCF-A)

    [C24] Yuanzhe Chen, Jun Kuang, Dawei Cheng, Jianbin Zheng, Ming Gao, and  Aoying Zhou. AgriKG: An Agricultural Knowledge Graph and Its Applications. DASFAA 2019. (CCF-B)

    [C22] Ming Gao, Leihui Chen, Xiangnan He, and Aoying Zhou. BiNE: Bipartite Graph Embedding. SIGIR 2018. (CCF-A)

    [C21] Jianbing Zheng, Yanbin Li, Yanji Hou, Ming Gao, and Aoying Zhou. BMNR: Design and Implementation a Benchmark for Metrics of Network Robustness. ICBK 2017. 

    [C20] Leihui Chen, Jianbing Zhen, Ming Gao, Aoying Zhou, Wei Zeng and Hui Chen. TLRec: Transfer Learning for cross-domain Recommendation. ICBK 2017.

    [C19] Lisi Ai, Na Li, and Ming Gao. Automatic Text Generation via Text Extraction Based on Submodular. APWeb 2017. (CCF-C)

    [C18] Jihong Yan, Yanhua Wang, Ming Gao, Aoying Zhou. Context-aware Entity Summarization. WAIM 2016. 517-529. (CCF-C)

    [C17] Chao Kong, Ming Gao, Weining Qian, Aoying Zhou. Entity Matching Across Multiple Heterogeneous Data Sources. DASFAA 2016. (CCF-B)

    [C16] Ming Gao, Ee-Peng Lim, David Lo, Feida Zhu, Philips Kokoh Prasetyo, Aoying Zhou, CNL: Collective Network Linkage across Heterogeneous Social Network. ICDM 2015. (CCF-B)

    [C15] Chao Kong, Ming Gao, Weining Qian, Minqi Zhou, Xueqing Gong, Rong Zhang, Aoying Zhou, ACID Encountering the CAP Theorem-Two Bank Case Studies. WISA 2015.

    [C14] Jinyang Li, Chengyu Wang, Xiaofeng He, Rong Zhang, Ming Gao, User Generated Content Oriented Chinese Taxonomy Construction. APWeb 2015. (CCF-C)

    [C13] Rong Zhang, Yifan Gao, Wenzhe Yu, Pingfu Cao, Xiao Yang, Ming Gao, Aoying Zhou, Review Comment Analysis for Predicting Rating. WAIM 2015. (CCF-C)

    [C12] Lei Wang, Ming Gao, Rong Zhang, Cheqing Jin, Aoying Zhou, Computing Probability Threshold Set Similarity on Probabilistic Sets. WAIM 2015. (CCF-C)

    [C11] Qiuge Song, Cheqing Jin, Xiaoling Wang, Ming Gao, and Aoying Zhou, Discovering Underpasses from Walking Trajectories. DAMASCA 2015.

    [C10] Chengyu Wang, Ming Gao, Xiaofeng He, and Rong Zhang, Challenges in Chinese Knowledge Graph Construction. DESWeb 2015.

    [C9] Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu, and Kazunari Sugiyama, Predicting the Popularity of Web 2.0 Items Based on User Comments. SIGIR 2014. (CCF-A)

    [C8] Philips Kokoh Prasetyo, Ming Gao, Ee-Peng Lim, and Christie Napa Scollon, Social  Sensing for Urban Crisis Management: The Case of Singapore Haze. The 5th International  Conference on Social Informatics (SocInfo 2013), November 25-27, 2013.

    [C7] Ming Gao, Ee-Peng Lim, and David Lo, R-energy for Evaluating Robustness of Dynamic  Networks. ACM Conference on Web Science, May 2-4, 2013.

    [C6] Ming Gao, Cheqing Jin, Wei Wang, Xuemin Lin, and Aoying Zhou, Similarity Query Processing for Probabilistic Sets. ICDE 2013. (CCF-A)

    [C5] Ming Gao, Cheqing Jin, Weining Qian, and Xueqing Gong, Real-time Search over a Microblogging System. CGC 2012: 352-359. (优秀论文奖)

    [C4] Cheqing Jin, Ming Gao, and Aoying Zhou, Handling ER-topk Query on Uncertain Streams. DASFAA 2011: 326-340. (CCF-B)

    [C3] Ming Gao, Xiangnan He, Cheqing Jin, Xiaoling Wang, and Aoying Zhou, Recording How- Provenance on Probabilistic Databases, APWEB 2010. (CCF-C)

    [C2] Peisen Yuan, Xiaoling Wang, Chaofeng Sha, Ming Gao, and Aoying Zhou, GRAMS3: An Efficient Framework for XML Structural Similarity Search. UDM 2010.

    [C1] Chen Zhang, Ming Gao, and Aoying Zhou, Tracking High Quality Clusters over Uncertain Data Streams. ICDE 2009: 1641-1648. (CCF-A)


    Publised Books:

    [B3] Ming Gao, Ee-Peng Lim, David Lo, Network Data Mining and Analysis, World Scientific 2018.

    [B2] Kun Yue, Weiyi Liu, Hao Wu, Dapeng Tao, Ming Gao, Discovery and Fusion of Uncertain Knowledge in Data, World Scientific 2017.

    [B1] 华东师范大学数据科学与工程研究院（译）. 海量数据分析前沿. 清华大学出版社，2015.



    Honor