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Richard A. Olshen

Academic Appointments

  • Professor of Health Research & Policy (Biostatistics) and, by courtesy, of Electrical Engineering and of Statistics

Key Documents

Contact Information

  • Academic Offices
    Personal Information
    Email Tel (650) 725-2241
    Alternate Contact
    Bonnie Chung Computing Information Systems Analyst Tel Work (650)723-5301

Bio

Olshen's research is in statistics and their applications to medicine and biology. Many efforts have concerned tree-structured algorithms for classification, regression, survival analysis, and clustering. Those for classification have been used with success in computer-aided diagnosis and prognosis, while those for clustering have been applied to lossy data compression in digital radiography. Modeling and sample reuse methods have been developed for longitudinal data, concerning gait analysis; renal physiology; cholesterol; nephrophysiology; and recently, molecular genetics.

Academic Appointments

Administrative Appointments

  • Chief, Division of Biostatistics, Department of Health Research and Policy, Stanford (1998 - present)
  • Director, Biostatistics Unit, UCSD Cancer Center (1978 - 1989)
  • Director, Laboratory for Mathematics and Statistics, University of California, San Diego (1982 - 1989)

Honors and Awards

  • Fellow, Institute of Electrical and Electronics Engineers (IEEE) (2006)
  • Fellow, American Statistical Association (1996)
  • Fellow, American Association for the Advancement of Science (1990)
  • Fellow, Institute of Mathematical Statistics (1973)
  • Fellowship, John Simon Guggenheim Memorial Foundation (1987-88)

Professional Education

Ph.D.: Yale University, Statistics (1966)

Research & Scholarship

Current Research and Scholarly Interests

My research is in statistics and their applications to medicine and biology. Many efforts have concerned tree-structured algorithms for classification, regression, survival analysis, and clustering. Those for classification have been used with success in computer-aided diagnosis and prognosis and for studies of complex human disease by association with single nucleotide polymorphisms and other predictors. Those for clustering have been applied to lossy data compression in digital radiography. Modeling and sample reuse methods have been developed for longitudinal data, concerning gait analysis; renal physiology; cholesterol; and molecular genetics.

Teaching

Courses

2013-14

Prior Year Coursescourses of Richard Olshen

Graduate and Fellowship Program Affiliations

Publications

Publications

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