Caroline Smith's Teaching Interests

• Current Courses (Fall 2002):
  CALCULUS II MATH236 , MATHEMATICAL MODELLING I MATH 115 .
  
  
• Other Recently Taught Courses:
  PARTIAL DIFFERENTIAL EQUATIONS MATH387 , COMPUTING AND NUMERICAL METHODS MATH248 , MATHEMATICAL MODELLING II MATH 341 and ELEMENTARY STATISTICS MATH220 .
  
  
  

• PhD Students Supervised:
  Navendhu Bhatt, Validating the Translation of Stakeholder Requirements to System Requirements , Stevens Institute of Technology, USA, current.
  
  John Baker, Random Effect Models for Repairable System Reliability, University of Plymouth, UK., November 1997.
  
  
• Masters Students Supervised:
  Luciano Pizziolo, A Statistical Analysis Methodology for Extension of Shelf/Service Life of Rocket Motors Based on Surveilllance Test Data , University of Exeter, UK., July 1999
  
  

• Short Courses Offered:
  Aeroacoustics, Fuzzy Logic, Computational Fluid Dynamics, Mathematical Modelling, Industrial Statistics, Reliability
  
  
  

• Short Courses Taught:
  
  M.Sc. Course Instructor (1992 – 1999), University of Exeter, Exeter, DEVON, United Kingdom.
  
  Course Instructor (1999-present):
  United Defense, Minneapolis, MN. Introduction to Statistics and Probability Concepts for Application to System Reliability, Maintainability and Supportability Analysis , two-day course, April 2000.
  
  United Defense, York,Probability and Statistical Tools , One-day course, October 1999.
  
  United Defense, Minneapolis, MN. Introduction to Statistics and Probability Concepts for Application to System Reliability, Maintainability and Supportability Analysis , two-day course, March 1999.
  
  Course Co-Instructor (1996-1997):
  University of Exeter, Exeter, DEVON, United Kingdom. Introduction to Proportional Hazards Modeling, System Operational Effectiveness Summer School
  
  University of Exeter, Exeter, DEVON, United Kingdom. Supportability: Engineering, Economics and Management”, Seventh International Summer School
  
  Rolls Royce, Derby , United Kingdom, Introduction to Statistics for Logisticians, three-day course.