Mingsheng Hong

Department of Computer Science
Cornell University

4104 Upson Hall
Ithaca, NY 14853

Email: mshong [at] cs.cornell.edu
Tel: (607) 255-9537

Welcome to my homepage!

 I am a fifth year Ph.D. student working with Prof. Johannes Gehrke on expressive and large-scale event stream processing. At Cornell, we have built Cayuga, an efficient, scalable system for pattern detection over event streams. I have also spent a few summers at MSR Redmond contributing to the Immortal DB transaction-time database project, and the CEDR stream processing project. 

The cayuga source code has been released! Also, please check out the 5-minute demo video on using Cayuga to monitor Blogosphere. The video accompanies our SIGMOD 07 Cayuga demo paper.

I expect to graduate in Summer 2008. Convinced by a series of pitches from Mike Stonebraker et al. -- "One Size Does not Fit All" Part 1, Part 2, and "The End of An Architecture Era" -- I am joining Vertica, the world's next generation database system.

Publications

Stateful Publish/Subscribe, Complex Event Stream Processing

• M. Hong, A. Demers, J. Gehrke, C. Koch, M. Riedewald, W. White. "Massively Multi-Query Join Processing in Publish/Subscribe Systems". SIGMOD 2007
• L. Brenna, A. Demers, J. Gehrke, M. Hong, J. Ossher, B. Panda, M. Riedewald, M. Thatte, W. White. "Cayuga: A High-Performance Event Processing Engine" (demo). SIGMOD 2007
• A. Demers, J. Gehrke, M. Hong, B. Panda, M. Riedewald, V. Sharma, W. White. "Cayuga: A General Purpose Event Monitoring System". CIDR 2007
• R. Barga, J. Goldstein, M. Ali, M. Hong. "Consistent Streaming Through Time -- A Vision for Event Stream Processing". CIDR 2007
• A. Demers, J. Gehrke, M. Hong, M. Riedewald, W. White. "Towards Expressive Publish/Subscribe Systems". EDBT 2006
• A. Demers, J. Gehrke, M. Hong, M. Riedewald. "Processing High-Speed Intelligence Feeds in Real-Time". ISI 2005

Data Mining

• W. Wang, Q. Yuan, H. Zhou, M. Hong, B. Shi: "Extracting Frequent Connected Subgraphs from Large Graph Sets". Journal of Computer Science and Technology, Volume 19, Number 6, 2004
• C. Wang, M. Hong, W. Wang, B. Shi. "Chopper: Efficient Algorithm for Tree Mining". Journal of Computer Science and Technology, Volume 19, Number 3, 2004.
• C. Wang, M. Hong, J. Pei, H. Zhou, W. Wang, B. Shi. "Efficient Pattern-Growth Methods for Frequent Tree Pattern Mining". In Proceedings of the Eighth Pacific-Asia Conference on Knowledge Discovery and Data Mining ( PAKDD'04)
• M. Hong, H. Zhou, W. Wang, B. Shi. "An Efficient Algorithm of Frequent Connected Subgraph Extraction". In Proceedings of the Seventh Pacific-Asia Conference on Knowledge Discovery and Data Mining ( PAKDD'03)

Research Experiences

• Summer 07: Microsoft Research Database Group. Research Intern. Mentor: Dr. Jonathan Goldstein
  • CEDR Event Processing Project
• Summer 06: Microsoft Research Database Group. Research Intern. Mentor: Dr. Roger Barga
  • CEDR Event Processing Project
• Summer 05: Microsoft Research Database Group. Research Intern. Mentor: Dr. David Lomet
  • Immortal DB Project
• Fall 03 - Present: Cornell Database Group. Research Assistant. Advisor: Prof. Johannes Gehrke
  • Cayuga Stateful Pub/Sub System
• Fall 02: Shanghai (International) Database Research Center. Research Assistant. Supervisor: Prof. Wei Wang, Dr. Haofeng Zhou
  • Frequent Sub-tree Pattern Mining
  • Frequent Sub-graph Pattern Mining

Teaching Experiences

Instructor

CS 215 (Introduction to C#): Spring 2008

CS 433 (Practicum in Database Systems): Fall 2006

Teaching Assistant

CS 432 (Introduction to Database Systems ): Fall 2006