Date: Thu, 07 Nov 1996 19:08:59 GMT Server: NCSA/1.5 Content-type: text/html Last-modified: Sun, 28 Jul 1996 00:44:15 GMT Content-length: 5864 Raghu Ramakrishnan's Home Page

Raghu Ramakrishnan

Associate Professor of Computer Science (raghu@cs.wisc.edu)

Department of Computer Sciences
University of Wisconsin - Madison

1210 West Dayton Street, Madison, WI 53706 USA

Phone: 608-262-9759 (Department: 262-1204, Fax: 262-9777)

Education:

Teaching Activities:

The text Database Management Systems, published by McGraw-Hill, is aimed at first and second courses in database systems at the undergraduate and graduate levels. The Minibase relational DBMS was developed in conjunction with this text. The Coral system is also used in courses that deal with logic databases at several schools.

Research Interests:

As the use of databases grows and diversifies, it is increasingly important to be able to access data from dispersed, heterogeneous, independently developed sources easily. In the RODIN project, and its successor, the C.O.D. project, I am investigating several issues: formal techniques and practical toolkits for semantic integration, supporting multiple levels of service and access to a database, and database access in a networked cluster of machines. This is joint work with Profs. Ioannidis and Livny.

In recent work, the results on visual data exploration from the NEXT! project, which is joint work with Prof. Livny, are being applied to data integration, and querying over the Web.

My second area of interest is content-based querying of complex data such as sequences and image sets. The SEQ system deals with queries over sequence data, and focuses on DBMS design and optimization issues related to sequence data. It is a part of the NEXT! project, and is joint work with Prof. Livny. An important aspect of this work is its use for identifying trends in the data, or in general, identifying useful patterns of information. In the PIQ project, the goal is to support content-based retrieval from large sets of images. Our focus is on developing and implementing an expressive data definition language that can be used to customize a general image database system to take advantage of specialized information about a given collection of images that is to be indexed and queried.

My interest in querying and analysis of data covers data exploration and mining. We have developed a powerful clustering algorithm called BIRCH for large datasets and a visual data exploration tool called DEVise as part of the NEXT! project. A long-standing research interest is the extension of relational database query languages with logic programming features such as structured terms and recursion, and the use of arithmetic constraints to specify data and queries more compactly and efficiently. An ongoing project involves the continued development and use of the CORAL deductive system. The evaluation is based upon bottom-up fixpoint evaluation techniques, and several optimizations are applied to make it efficient across a broad range of programs.

Research Projects:

Ph.D. Graduates