People

Fereidoon (Fred) Sadri

Fereidoon (Fred) Sadri

Professor, 1994
Ph.D. in Electrical Engineering (Computer Science), Princeton University (1980)

Office: Petty 204
Email: f_sadri@uncg.edu
Website

Research: Database and knowledge-base systems, information integration, modeling uncertainty in databases, deductive databases
Teaching: Databases and Foundations of Computer Science


Research Overview

Prof. Sadri’s research has included work in modeling and management of uncertain information in database systems, addressing the handling of inaccurate information in databases. Data is often uncertain, in particular when it is obtained by means of data mining and automated information extraction. Prof. Sadri has developed an approach which is based on solid mathematical probability theory for the representation of inaccurate data and query processing for uncertain data. In other work, Prof. Sadri has investigated issues related to multi-database systems, developing powerful database query languages that allow data/metadata transformation (such as the pivot and unpivot operations), and studying query optimization for these languages. This research forms the basis for interoperability among multiple database systems with different schemas.

In Prof. Sadri’s work on information integration from multiple sources, he considers the need for scalable decentralized data sharing which arises naturally in a wide range of applications, including enterprise data management, scientific projects undertaken across universities or research labs in biology, astronomy, and other domains, and data sharing among governmental databases. We have developed a framework and have implemented a system for a simple, intuitive, and efficient user interface to query a possibly large number of information sources without any knowledge of data representation details in these sources.

Prof. Sadri’s most recent research has been on high-speed parallel processing of very large volumes of data using the “Map-Reduce” technique that was introduced by Google. In this approach, data is partitioned among large numbers (tens or even hundreds of thousands) of desktop computers that collectively process the data efficiently.

Research Support

Prof. Sadri’s research has been supported by the National Science Foundation (NSF), Bell Northern Research, IBM, Natural Science and Engineering Council of Canada.

About

Prof. Sadri received his Ph.D. and M.S. degree in Electrical Engineering and Computer Science from Princeton University in 1980 and 1978, respectively. He received his B.S. degree in Electrical Engineering from Tehran University, Iran in 1972.