Database Systems Research Group (DSRG)
Welcome to the WPI Database Systems Research Group. We are a group of faculty, researchers, and students who are working on database projects. Our group focuses on research issues and project work related to very large database and information systems in support of advanced applications including business, engineering, and sciences, large-scale data analytics, scientific data management, annotation and provenance management, multi-dimensional query processing and optimizations. Currently on-going projects include intelligent event analytics, scalable data stream processing systems, map-reduce technologies, biological databases, stream mining and discovery, large-scale visual information exploration, medical process tracking, and distributed heterogeneous information sources, to just name a few. We thrive to build software systems to evaluate the feasibility of our innovations and to evaluate their usefulness by applying them to real problems.
Announcement:
CONGRATULATIONS: Venkatesh (Venky) Raghavan's Final Ph.D. Dissertation Defense. It gives me great pleasure to announce that Venky Raghavan has successfully passed his final Ph.D. Dissertation Defense, Thursday, April 5th 2012. Congratulations to Dr. Venkatesh Raghavan! Congratulations to Venky on having successfully conducted high-quality and innovative research, which has been published in top venues, including ICDE, Information Systems Journal, IDAR, and others, and several very well-received software demonstrations of core technologies in ACM SIGMOD. Venky's dissertation research falls in the area of big-data analytics and multi-criteria preference systems. His dissertation is entitled "Supporting Multi-Criteria Decision Support Queries over Disparate Data Sources". Given the exponential growth of information, providing services to help analysts, businesses and users alike to extract value from data is imperative for staying ahead and meeting one's information needs. In this context, Venky has designed a suite of innovative techniques and corresponding software technologies that tackle open problems in support of multi-dimensional preference (skyline) queries, enabling users to quickly grasp their prefered choices from a huge data store. Venky has started his professional career at the Greenplum startup (now, an EMC company) in California, and is enjoying every day of it. He is getting his hands deep into the guts of a commercial query optimizer for large-scale distributed compute platforms - helping to build it from the grounds up to meet the BigData buzz. We wish him the very best success and fun in his future professional career in computing ! We also would like to thank everyone who was able to attend Venky's defense yesterday and lend their support to him. We thank the CS department, all faculty, the office and computing staff, for providing an amazingly nuturing environment in which Venky could mature into an accomplished researcher and Computer Scientist. It sure was a pleasure yesterday seeing Venky shine in his accomplishments -- he has come a long way, and I am proud of him. In particular, we thank the committee members Prof. Dan Dougherty, Prof. Murali Mani and Dr. Haixun Wang (Microsoft Research Asia) for their time, effort and extremely valuable feedback on Venky's work. Their help in guiding Venky is very much appreciated.
CONGRATULATIONS: Mo Liu's Final Ph.D. Dissertation Defense. It gives me great pleasure to announce that Liu Mo has successfully passed her final Ph.D. Dissertation Defense today, Tuesday, March 7th 2012. The committee has accepted her work subject to minor revisions, which Mo plans to apply to the manuscript in the following weeks. Congratulations to soon-to-be Dr. Liu! Congratulations to Mo on having conducted high-quality research, which has been published in top venues in the database field, including SIGMOD, ICDE, and others. Mo's dissertation research falls in the area of Complex Event Processing on Data Streams. Specifically, her dissertation entitled "Extending Event Sequence Processing: New Models and Optimization Techniques" includes the design, development and evaluation of several techniques at the core of an E-Analytic system to achieve efficient, scalable and robust methods for in-memory multi-dimensional nested pattern analysis over high-speed event streams. We would like to thank everyone who was able to attend Mo's defense and lend their support to Mo. We thank the CS department for providing a nuturing environment in which Mo Liu could mature into an accomplished Computer Scientist. In particular, we thank the committee members Prof. Dan Dougherty, Prof. Yanlei Diao, University of Massachusetts Amherst; Prof. Murali Mani, University of Michigan, Flint; and Prof. Ismail Ari, Ozyegin University, Turkey for their time and valuable feedback on Moi's work. In particular, Mo would like to extend a special thank you to Prof. Dan Dougherty, who has spent countless hours in helping Mo to explore the world of CEP language design, semantics and optimization. The committee's help in guiding Mo to make her work of the utmost quality is much appreciated. Lastly, Mo Liu has started her professional career at Sybase, Inc, an SAP Company, in California. We wish her a fulfilling career complete with interesting challenges and both success and fun going forward, where ever life may take her.
CONGRATULATIONS: Di Yang's Final Ph.D. Dissertation Defense It gives me great pleasure to announce that Di Yang has successfully passed his final Ph.D. Dissertation Defense today, Friday, Jan 6th 2012. Congratulations to soon to be Dr. Yang! Congratulations to Di on having successfully conducted high-quality research, which has been published in top venues, including VLDB, SIGMOD, EDBT, CIKM, and ACM TODS in the database field. Di's dissertation research falls in the intersection of data mining and data stream processing. In particular, his dissertation is on "Mining and Managing Neighbor-Based Patterns in Data Streams". His work includes the design, development and evaluation of algorithms for efficiently executing neighbor-based pattern mining requests, including popular pattern types like clusters, outliers, and k-nearest neighbors. Second, he tackles the problem of multiple query optimization for neighbor-based pattern mining requests with arbitrary parameter settings. Lastly, he develops efficient mechanisms to match in real-time a pattern of interest against previously discovered and summarized patterns in a pattern archive. Di has started his professional career at Oracle Corporation in Nashua, NH. We wish him the very best success and fun in his future career, where ever it may take him! We would like to thank everyone who was able to attend Di's defense and lend their support to him. We thank the CS department for providing a nurturing environment in which Di Yang could mature into an accomplished researcher and Computer Scientist. In particular, we thank the committee members Prof. Matt Ward, Prof. Dan Dougherty, and the external member Prof. Evimaria Terzi from Boston University for their time, effort and extremely valuable feedback on Di's work. Their help in guiding Di has been tremendous and is very much appreciated.
Current Projects:
- CEA: Complex Event Analytics
- QueryMesh: A Novel Paradigm for Query Processing
- RAINDROP: XQueries Over XML Streams (Automaton Meets Algebra)
- CAPE: Continuous Adaptive Processing Engine
- XMDV: Visual Exploration Support for Data Mining and Discovery
- more...
Latest Publications
- Rimma Nehme, Karen Works, Elke A. Rundensteiner, Elisa Bertino, Chuan Lei. Multi-Route Query Processing and Optimization. Journal of Computer and System Sciences (JCSS), 2012, .
- Medhabi Ray, Mo Liu, Elke Rundensteiner, etc. , Realtime Healthcare Services Via Nested Complex Event Processing Technology. EDBT Demonstration, 2012, .
- Di Yang, Elke A. Rundensteiner, Matthew O. Ward. Shared execution strategy for neighbor-based pattern mining requests over streaming windows.. 5, 2012, ACM Trans. Database Syst., .
- Di Wang, Lei Cao, Qingyang Wang, Elke Rundensteiner. QoX Driven Framework for Sensor Event Stream Analytics. SIAM Data Mining 2012, 1st International Workshop on Analytics for Cyber-Physical Systems, 2012, .
- Karen Works, Elke A. Rundensteiner, and Emmanuel Agu. Optimizing Adaptive Multi-Route Query Processing via Time-Partitioned Indices. Journal of Computer and System Sciences, 2012, .
Elke Rundensteiner Wins 2007 Creative
Scholarship Award
The Computer Science Department is very
pleased and proud to announce that Professor Elke Rundensteiner is the
winner of the 2007 Board of Trustees' Award for Outstanding Research and
Creative Scholarship. The full citation for the award mentions her
seminal work, and her international reputation as a scholar in the area
of databases. More than 20 external scholars provided glowing letters of
recommendation. One of Elke's ex-PhD students said that "Elke is a
source of inspiration, a mentor and a superb role model".