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EDUCATION
Ph.D. New York University.
(1968)
M.S. Rutgers
University.
(1964)
B.S. B.V.B. College, India.
(1959)
TITLES
Director, Institute for Reliability and Risk Analysis.
Distinguished Research Professor & Professor of Statistics, and
Decision Sciences.
BIOGRAPHY
Nozer D. Singpurwalla is Professor of Statistics and Distinguished Research
Professor at the George
Washington University
in Washington, D.C.
He has been Visiting Professor at Carnegie-Mellon
University, Stanford
University, the University
of Florida at Tallahassee,
the University of California
at Berkeley, the
Santa Fe Institute and Oxford
University (UK).
During Fall 1991, he was the first C. C. Garvin Visiting Endowed Professor
in the Mathematical Sciences at the Virginia Polytechnic Institute and
State University. He is Fellow of the Institute
of Mathematical Statistics,
the American Statistical Association, and the American Association for the
Advancement of Science, and he is an elected member of the International
Statistical Institute. He is the 1984 recipient of the U.S. Army's S. S.
Wilks Award for Contributions to Statistical Methodologies in Army
Research, Development and Testing, and the first recipient of The George
Washington University's Oscar and Shoshana Trachtenberg Prize for Faculty
Scholarship. He has coauthored two books in reliability and has published
over 175 papers on reliability theory, warranties, failure data analysis,
Bayesian statistical inference, dynamic models and time series analysis,
quality control and statistical aspects of software engineering. In 1993 he
was selected by the National Science Foundation, the American Statistical
Association and the National Institute of Standards and Technology as the
ASA/NIST/NSF Senior Research Fellow. In 1993 he was awarded a Rockefeller
Foundation Grant as a Scholar in Residence at the Bellagio, Italy
Center.
RESEARCH INTERESTS
Specialty areas: Applied probability and Bayesian statistics;
reliability theory, warranties, and quality control; time series analysis;
fault tree analysis; filtering theory; uncertainty in expert systems, and
failure data analysis.
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