Professors Goodrich, Tamassia, and Mount are well-recognized researchers in data structures and algorithms, having published many papers in this field, with applications to Internet computing, information visualization, geographic information systems, computer security, and computer graphics. They have an extensive record of research accomplishments and have served as principal investigators in several projects sponsored by the National Science Foundation, the Army Research Office, and the Defense Advanced Research Projects Agency. They are also active in educational technology research, with special emphasis on algorithm visualization.
Michael Goodrich received his Ph.D. in Computer Science from Purdue University in 1987. He is currently a professor in the Department of Information and Computer Science at University of California, Irvine. Prior to this service, he was a professor of Computer Science at Johns Hopkins University and codirector of the Hopkins Center for Algorithm Engineering. He is an editor for the International Journal of Computational Geometry & Applications and Journal of Graph Algorithms and Applications.
Roberto Tamassia received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 1988. He is currently a professor in the Department of Computer Science and the director of the Center for Geometric Computing at Brown University. He serves as an editor for Computational Geometry: Theory and Applications and as editor-in-chief of the Journal of Graph Algorithms and Applications. He previously served on the editorial board of IEEE Transactions on Computers.
David Mount received his Ph.D. in Computer Science from Purdue University in 1983. He is currently a professor in the Department of Computer Science at the University of Maryland with a joint appointment in the University of Maryland's Institute for Advanced Computer Studies. He is an associate editor for Pattern Recognition.
In addition to their research accomplishments, the authors also have extensive experience in the classroom. For example, Dr. Goodrich has taught data structures and algorithms courses at Johns Hopkins University and at the University of California, Irvine since 1987, including Data Structures as a freshman-sophomore level course and Introduction to Algorithms as an upper-level course. He has earned several teaching awards in this capacity. His teaching style is to involve the students in lively interactive classroom sessions that bring out the intuition and insights behind data structuring and algorithmic techniques, as well as in formulating solutions whose analysis is mathematically rigorous.
Dr. Tamassia has taught Data Structures and Algorithms as an introductory freshman-level course at Brown University since 1988. He has also attracted many students to his advanced course on Computational Geometry. One thing that has set his teaching style apart is his effective use of interactive hypermedia presentations, continuing the tradition of Brown's "electronic classroom." The carefully designed Web pages of the courses taught by Dr. Tamassia have been used as reference material by students and professionals worldwide.
Dr. Mount has taught both the Data Structures and the Algorithms
courses at the University of Maryland since 1985. He has won a number
of teaching awards from Purdue University, the University of Maryland,
and the Hong Kong University of Science and Technology. His lecture
notes and homework exercises for the courses that he has taught are
widely used as supplementary learning material by students and
instructors at other universities.