Yang Zhou

College of Computing
Georgia Institute of Technology

3012, Klaus Advanced Computing Building
266 Ferst Drive
Atlanta, GA 30332-0765

Email: yzhou@gatech.edu


Biography

I am currently a Ph.D. student in the College of Computing at the Georgia Institute of Technology, under the supervision of Prof. Ling Liu.


Research Interests
Big Data Analytics, Graph Processing System, Graph Mining Algorithm, Web Services, Cloud Computing

Professional Services
  • IEEE Member.
  • Invited reviewer of ACM Transactions on Knowledge Discovery from Data (TKDD).
  • Invited reviewer of IEEE Transactions on Dependable and Secure Computing (TDSC).
  • Invited reviewer of IEEE Transactions on Services Computing (TSC).
  • External reviewer of KDD, ICDM, PAKDD, VLDB, ICDE, EDBT, ICDCS, WISE, IDEAS, ACML, Computational Intelligence.

Awards
  • Georgia Tech Graduate Student Travel Award, 2014.
  • Winner of Invention Day Patent Marathon, IBM Almaden Research Center, 2013.
  • First Patent Application Invention Achievement Award, IBM, 2013.
  • ICWS Student Travel Award, 2013.
  • ICDM Student Travel Award, 2010.

Publications (DBLP) (Google Scholar)
  • Kisung Lee, Ling Liu, Karsten Schwan, Calton Pu, Qi Zhang, Yang Zhou, Emre Yigitoglu, Pingpeng Yuan. Scaling Iterative Graph Computations with GraphMap. To appear in Proceedings of the 27th IEEE international conference for High Performance Computing, Networking, Storage and Analysis (SC'15). (full paper).

  • Yang Zhou, Ling Liu, Kisung Lee and Qi Zhang. GraphTwist: Fast Iterative Graph Computation with Two-tier Optimizations. To appear in Proceedings of the 41st International Conference on Very Large Data Bases (VLDB'15). (full paper).

  • Yang Zhou, Ling Liu and David Buttler. Integrating Vertex-centric Clustering with Edge-centric Clustering for Meta Path Graph Analysis. To appear in Proceedings of the 21st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'15). (full paper).

  • Yang Zhou and Ling Liu. Social Influence Based Clustering and Optimization over Heterogeneous Information Networks. To appear in ACM Transactions on Knowledge Discovery from Data (TKDD), 2015.

  • Yang Zhou, Ling Liu, Calton Pu, Xianqiang Bao, Kisung Lee, Balaji Palanisamy, Emre Yigitoglu and Qi Zhang. Clustering Service Networks with Entity, Attribute and Link Heterogeneity. Proceedings of the 22nd IEEE International Conference on Web Services (ICWS'15). (full paper).

  • Xianqiang Bao, Ling Liu, Nong Xiao, Yang Zhou and Qi Zhang. Policy-driven Autonomic Configuration Management for NoSQL. Proceedings of the 2015 IEEE International Conference on Cloud Computing (CLOUD'15). (full paper).

  • Yang Zhou, Ling Liu, Kisung Lee, Calton Pu and Qi Zhang. Fast Iterative Graph Computation with Resource Aware Graph Parallel Abstractions. Proceedings of the 24th ACM Symposium on High-Performance Parallel and Distributed Computing (HPDC'15). (one of only 19 full papers).

  • Zhiyuan Su, Ling Liu, Mingchu Li, Xinxin Fan and Yang Zhou. Reliable and Resilient Trust Management in Distributed Service Provision Networks. ACM Transactions on the Web (TWEB), 9(3), 2015.

  • Yang Zhou and Ling Liu. Activity-edge Centric Multi-label Classification for Mining Heterogeneous Information Networks. Proceedings of the 20th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'14). (full paper).

  • Yang Zhou, Sangeetha Seshadri, Lawrence Chiu and Ling Liu. GraphLens: Mining Enterprise Storage Workloads Using Graph Analytics. Proceedings of the 2014 IEEE International Congress on Big Data (BigData'14). (full paper).

  • Qi Zhang, Ling Liu, Kisung Lee, Yang Zhou, Aameek Singh, Nagapramod Mandagere, Sandeep Gopisetty and Gabriel Alatorre. Improving Hadoop Service Provisioning in a Geographically Distributed Cloud. Proceedings of the 2014 IEEE International Conference on Cloud Computing (CLOUD'14). (full paper).

  • Balaji Palanisamy, Ling Liu, Kisung Lee, Shicong Meng, Yuzhe Tang and Yang Zhou. Anonymizing Continuous Queries with Delay-tolerant Mix-zones over Road Networks. Distributed and Parallel Databases (DAPD), 32(1), 2014.

  • Yang Zhou and Ling Liu. Social Influence Based Clustering of Heterogeneous Information Networks. Proceedings of the 19th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD'13). (full paper).

  • Yang Zhou, Ling Liu, Chang-Shing Perng, Anca Sailer, Ignacio Silva-Lepe and Zhiyuan Su. Ranking Services by Service Network Structure and Service Attributes. Proceedings of the 20th IEEE International Conference on Web Services (ICWS'13). (full paper).

  • Zhiyuan Su, Ling Liu, Mingchu Li, Xinxin Fan and Yang Zhou. ServiceTrust: Trust Management in Service Provision Networks. Proceedings of the 10th IEEE International Conference on Services Computing (SCC'13). (full paper).

  • Kisung Lee, Ling Liu, Yuzhe Tang, Qi Zhang and Yang Zhou. Efficient and Customizable Data Partitioning Framework for Distributed Big RDF Data Processing in the Cloud. Proceedings of the 2013 IEEE International Conference on Cloud Computing (CLOUD'13). (full paper).

  • Qi Zhang, Ling Liu, Yi Ren, Kisung Lee, Yuzhe Tang, Xu Zhao and Yang Zhou. Residency Aware Inter-VM Communication in Virtualized Cloud: Performance Measurement and Analysis. Proceedings of the 2013 IEEE International Conference on Cloud Computing (CLOUD'13). (full paper).

  • Hong Cheng, Yang Zhou, Xin Huang and Jeffrey Xu Yu. Clustering Large Attributed Information Networks: An Efficient Incremental Computing Approach. Data Mining and Knowledge Discovery (DMKD), 25(3), 2012.

  • Yang Zhou and Ling Liu. Data Mining: Foundations and Intelligent Paradigms: Volume 1: Clustering, Association and Classification. Intelligent Systems Reference Library. Dawn E. Holmes and Lakhmi C. Jain. Springer, 2011.

  • Hong Cheng, Yang Zhou and Jeffrey Xu Yu. Clustering Large Attributed Graphs: A Balance Between Structural and Attribute Similarities. ACM Transactions on Knowledge Discovery from Data (TKDD), 5(2), 2011.

  • Yang Zhou, Hong Cheng and Jeffrey Xu Yu. Clustering Large Attributed Graphs: An Efficient Incremental Approach. Proceedings of the 10th IEEE International Conference on Data Mining (ICDM'10). (full paper).

  • Yang Zhou, Hong Cheng and Jeffrey Xu Yu. Graph Clustering Based on Structural/Attribute Similarities. Proceedings of the 35th International Conference on Very Large Data Bases (VLDB'09). (full paper).

  • Hong Cheng, David Lo, Yang Zhou, Xiaoyin Wang and Xifeng Yan. Identifying Bug Signatures Using Discriminative Graph Mining. Proceedings of the 18th International Symposium on Software Testing and Analysis (ISSTA'09). (full paper).

  • Guo Ping, Zhou Yang and Jun Zhuang. Mining Maximal and Closed Frequent Free Subtrees. Dynamics of Continuous, Discrete and Impulsive Systems (DCDIS), 14(S1), 2007.

  • Yang Zhou and Feng Wang. FSM-A Frequent Subgraph Mining Algorithm Based on Subgraph and Structure Isomorphism. Journal of Computer Research and Development (JCRD), 44(z3), 2007.

  • Ping Guo, Yang Zhou, Jun Zhuang, Ting Chen and Yan-Rong Kang. An Efficient Algorithm for Mining both Closed and Maximal Frequent Free Subtrees Using Canonical Forms. Proceedings of the International Conference on Advanced Data Mining and Applications (ADMA'05). (full paper).

  • Ping Guo, Ting Chen, Yang Zhou and Dong Li. Adaptive Ants Clustering Algorithm Miming Correlative Page Set. Proceedings of the 11th Joint International Computer Conference (JICC'05). (full paper).

  • Guo Ping, Zhuang Jun, Zhou Yang, Zhou Jin and Cai Ri Xu. Mining Sequence Pattern of Router Logs. Computer Science, Vol.11, 2005.

  • Ping Guo, Yang Zhou and Jun Zhuang. Mining both Closed and Maximal Frequent Free Subtrees. Proceedings of the 2004 International Symposium on Computational Intelligence and Industrial Application (ISCIIA'04). (full paper).


Projects
  • GraphTwist: Fast Iterative Graph Computation with Two-tier Optimizations. Georgia Institute of Technology, 2014.

  • VEPathCluster: Integrating Vertex-centric Clustering with Edge-centric Clustering for Meta Path Graph Analysis. Georgia Institute of Technology, Lawrence Livermore National Laboratory, 2014.

  • ServiceCluster: Clustering Service Networks with Entity, Attribute and Link Heterogeneity. Georgia Institute of Technology, 2014.

  • AEClass: Activity-edge Centric Multi-label Classification for Mining Heterogeneous Information Networks. Georgia Institute of Technology, 2013.

  • GraphLens: Understanding Enterprise Storage Workloads Using Graph Analytics. IBM Almaden Research Center, San Jose, CA, 2013.

  • SAS-Ranking: Structure and Attribute Ranking of RDF Services by Service Provisioning Similarity. IBM T.J. Watson Research Center, Hawthorne, NY, 2012.

  • Cloud Services Marketplace. IBM T.J. Watson Research Center, Hawthorne, NY, 2012.

  • SI-Cluster: Social Influence Based Clustering of Heterogeneous Information Networks. Georgia Institute of Technology, 2012.

  • Inc-Cluster: Clustering Large Attributed Graphs: An Efficient Incremental Approach. Chinese University of Hong Kong, 2010.

  • SA-Cluster: Graph Clustering Based on Structural/Attribute Similarities. Chinese University of Hong Kong, 2009.


Patents
  • YOR820120928, Interactive Acquisition of Remote Services.
  • YOR820120950, Complex Service Network Ranking and Clustering.

Courses

Links