Wang-Chien Lee (李旺謙), Associate Professor
W332 Westgate Building
Department of Computer Science and Engineering
The Pennsylvania State University
University Park, PA 16802, USA
E-mail: wlee@cse.psu.edu Web: https://sites.psu.edu/wlee
Tel: (814) 865-1053 Fax: (814) 865-3176
Education
- Ph.D., 1996, Dept. of Computer & Information Science, Ohio State University, Columbus, Ohio, USA.
- M.S., 1989, Department of Computer Science, Indiana University, Bloomington, Indiana, USA.
- B.S., 1985, Department of Information Science, National Chiao-Tung University, Hsinchu, Taiwan.
Research
Dr. Lee leads the Intelligent Pervasive Data Access (iPDA) Research Group at Penn State to pursue cross-area research in big data management, pervasive/mobile computing, and networking. His primary research include:
- Network Representation Learning https://sites.psu.edu/ipda/projects/nrl/
- Intelligent Transportation Systems and Trajectory Mining
- Social Network Data Analytics
- Patent Mining
- Mobile and Pervasive Data Access
- Location-Based Services
- Peer-to-Peer (P2P) Computing
- Wireless Sensor Networks
- Time-Critical and Secure Wireless Data Broadcast
- Information Retrieval Visualization and Analysis
More details about his recent research activities can be found in the iPDA research group web site. https://sites.psu.edu/ipda
Funding
- Principal Investigator, Learning Latent Representations of Heterogeneous Information Networks, (Co-PI: Zhen Lei), NSF, IIS-1717084, 8/2017 – 7/2020, $499,635. Project Website: https://sites.psu.edu/ipda/projects/nrl/
- Co-PI, Impacts of the NIH Public Access Policy on Knowledge Flow and Diffusion in Academic and Industrial Research, (PI: Zhen Lei), NSF, SMA-1360205, 5/2014 – 4/2017, $619,767.
- Principal Investigator, Link Quality Estimation for Wireless Sensor Networks, NSF, CNS-0626709, 9/2006-8/2009, $250,000.
- Principal Investigator, Indexing Multi-Dimensional Data in Peer-to-Peer Systems, (Co-PI: Anand Sivasubramaniam), NSF, IIS-0534343, 1/2006-12/2008, $330,000.
- Principal Investigator, Location-based Information Access in Pervasive Computing Environments, NSF, IIS-0328881, 9/2004- 8/2007, $265,000.
- Co-Investigator, ECOQUAD: Energy-Conserving Quality-Aware Data Collection in Wireless Sensor Networks, (PI: Jianliang Xu), Research Grants Council (Hong Kong), 9/2005-8/2007, HK$ 391,000.
- Senior Personnel, STNexus: An Integrated Database and Visualization Environment for Space-Time Information Exploitation, (PIs: Donna J. Peuquet and Alan M. MacEachren), Advanced Research and Development Activity, NSA/NGA/CIA, 6/2005-5/2007, $806,000.
- Co-Investigator, Wireless Information Publication and Access, (PI: Dik Lee), Research Grants Council (Hong Kong), 9/2003-8/2005, HK$ 414,000.
- Co-Principal Investigator, Bioinformatics Consortium to Enhance Translational and Clinical Research (PI: Raj Archaya), Public Health Service, 7/2002-6/2005, $358,000.
- Co-Investigator, Modeling and Service Discovery in Pervasive Computing, (PI: Dik Lee), Research Grants Council (Hong Kong), 9/2001-8/2003, HK$390,000.
- Principal Investigator, Web Content Transformation Technology Evaluation Services, Genuity Inc., 7/2000-6/2001, $180,000.
Patents
- W.-C. Lee, G. Mitchell, X. Zhang, System and Method for Automatic Loading of an XML Document Defined by a Document-Type Definition into a Relational Database Including the Generation of a Relational Schema Therefor, United State Patent: 7072896B2.
- W.-C. Lee, G. Mitchell, E. Rundersteiner, X. Zhang, System and Method for Automatic Synchronizing and/or updating an Existing Relational Database with Supplemental XML Data, United State Patent: 7031956B1.
Selected Publication
- Chiang, M., Lim, E., Lee, W., Ashok, X., Prasetyo, P. (2019). One-Class Order Embedding Learning for Dependency Relation Prediction, Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019, July 21-25, 2019, Paris, France. Association for Computing Machinery.
- Ma, Q., Gu, Y., Lee, W., & Ge, Y. (2019). Order-Sensitive Imputation for Clustered Missing Values. IEEE Transaction on Knowledge and Data Engineering (TKDE). 31(1), pp.166-180.
- Kao, J., Ooi, B.C., Shen, Y., & Lee, W. (2018). Cuckoo Feature Hashing: Dynamic Weight Sharing for Sparse Analytics. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, IJCAI 2018, July 13-19, 2018, Stockholm, Sweden. The AAAI Press. Acceptance rate: 20.5%
- Luo, Z., Cai, S., Gao, J., Zhang, M., Ngiam, K.Y., Chen, G., & Lee, W. (2018). Adaptive Lightweight Regularization Tool for Complex Analytics. International Conference on Data Engineering, ICDE 2018, Paris, France. IEEE Computer Society. The Best Paper Award – Runner Up
- Lin, Y.-S., Yin, P., & Lee, W. (2018). Modeling Dynamic Competition on Crowdfunding Markets. Proceedings of the International Conference on World Wide Web, WWW 2018, Leon, France. ACM.
- Shuai, H.-H., Shen, C.-Y., Yang, D.-N., Lan, Y.-F., Lee, W., Yu, P. S., & Chen, M.-S. (2018). A Comprehensive Study on Social Network Mental Disorders Detection via Online Social Media Mining. IEEE Transaction on Knowledge and Data Engineering (TKDE), 30(7).
- Zhu, H., Yang, X., Wang, B., & Lee, W. (2018). Range-based Nearest Neighbor Queries with Complex-shaped Obstacles. IEEE Transaction on Knowledge and Data Engineering (TKDE), 30(5).
- Zhu, Q., Hu, H., Xu, J., & Lee, W. (2017). Geo-Social Group Queries with Minimum Acquaintance Constraint. The VLDB Journal, 26(5).
- Chiang, M.-F., Lim, E.-P., Lee, W., Kwee, A.T. (2017). BTCI: a New Framework for Identifying Congestion Cascades Using Bus Trajectory Data. Proceedings of IEEE International Conference on Big Data, BigData 2017, Boston, MA, USA. IEEE Computer Society. (Acceptance rate: 18%)
- Rengasamy, V., Fu, T.-Y., Lee, W., Madduri, K. (2017). Optimizing Word2Vec Performance on Multicore Systems. Proceedings of the Seventh Workshop on Irregular Applications: Architectures and Algorithms. Association for Computing Machinery. The Best Artifact Award.
- Fu, T.-Y., Lee, W., & Lei, Z. (2017). HIN2Vec: Explore Meta-paths in Heterogeneous Information Networks for Representation Learning. Proceedings of the ACM 2017 International Conference on Information and Knowledge Management, CIKM 2017. Association for Computing Machinery. Acceptance rate: 171/820=21%
- Shen, C.-Y., Huang, L.-H., Yang, D.-N., Shuai, H.-H., Lee, W., & Chen, M.-S. (2017). On Finding Socially Tenuous Groups for Online Social Networks. Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, KDD 2017. (pp. 415-424). Association for Computing Machinery. Acceptance rate: 64/748 = 8.6%