dietrich@asu.edu 
602-543-5628
602-543-3260
Suzanne W. Dietrich is an Associate Professor in the Department of Mathematical Sciences and Applied Computing at Arizona State University. She received her B.S. degree in computer science and applied mathematics in 1983 as valedictorian from the State University of New York at Stony Brook, and as the recipient of an Office of Naval Research Graduate Fellowship, earned her Ph.D. degree in computer science at Stony Brook in 1987. She then joined the faculty of the Department of Computer Science and Engineering at Arizona State University, where she established her teaching and research interests in the educational, practical and theoretical aspects of databases. In August 2005, Dr. Dietrich joined the Department of Mathematical Sciences and Applied Computing at ASU to contribute to the new Applied Computing Program at the West campus.
Currently, her research is breaking the database out of the box. Dr. Dietrich's interests emphasize incremental monitoring of conditions and evaluation of rules in active environments that respond to events and streaming information, such as in dataspaces and Grid-based virtual organizations. Her educational efforts focused on the development of the WinRDBI (http://www.eas.asu.edu/~winrdbi) educational tool for understanding relational database query languages and the development of a national model for an advanced database course for undergraduates (http://www.eas.asu.edu/~advdb), including object-oriented conceptual data models (EER and UML), object-oriented databases, object-relational databases and databases and the Web (JDBC and XML).
Dr. Dietrichs research has been supported by grants from the National Science Foundation. She has numerous journal and conference publications on her database and educational research and is the author of two database textbooks, entitled Understanding Relational Database Query Languages and An Advanced Course in Database Systems: Beyond Relational Databases. Dr. Dietrich is a member of the ACM, the ACM Special Interest Group on the Management of Data (SIGMOD), and the ACM Special Interest Group on Computer Science Education (SIGCSE).
Publications