RESUME OF DONALD R. SCOTT RESUME OF DONALD R. SCOTT
8505 Bobcat Drive, Round Rock, Texas 78681-3667
EDUCATION: B. A. Rice University, Houston, Texas and University of Texas, Austin, Texas. M.S., Ph. D., Physical Chemistry with Analytical minor, University of Houston. Postdoctoral, Theoretical Chemistry, University of Texas, Austin.
HONORS: Honor Teacher, Texas Tech University. Outstanding and Superior Performance Awards, U. S. EPA, 1981, 1984, 1987, 1993. Center of Excellence in Chemometrics, U. S. EPA, 1993-94. Associate Editor of Chemometrics and Intelligent Laboratory Systems, 1989-1997. Member Editorial Board, 1997- 1999.
EXPERTISE: Physical- Analytical Chemistry- Spectral and other analytical data analysis by pattern recognition, information theory and expert system techniques.
EXPERIENCE:
Industrial - Research Chemist, Texaco Production Research Lab., Bellaire, Texas, 1956-61. Visiting Professor, Phillips Petroleum Research Lab., Bartlesville, Oklahoma, summer, 1966. Principal Investigator, Lockheed Materials Sciences Lab., Marietta, Georgia, 1967-71.
Governmental - Supervisory Research Chemist, U. S. Environmental Protection Agency, Research Triangle Park, North Carolina, 1971-73, 1980-81; Las Vegas, Nevada, l975-78. Research Chemist and Senior Science Advisor, Research Triangle Park, North Carolina, 1981- 92. Senior Research Chemist, 1992 - 94.
Academic - Instructor, University of Texas, Austin, 1964-65. Assistant Professor, physical chemistry, Texas Tech University, Lubbock, 1965-67. Associate Professor, physical chemistry, South Dakota Tech., Rapid City, 1973-75. Adjunct Professor and Analytical Lab. Director, North Texas State University, Denton, 1978-80.
PUBLICATIONS: One monograph, seven book contributions, forty technical articles. Topics include quantum chemistry, electronic spectroscopy and electronic structure of metallocenes, environmental analytical chemistry including high resolution optical spectroscopy, pattern recognition of mass spectra, expert systems to identify toxic organic compounds and to predict molecular weights and their bounds for unknowns from mass spectral data.
