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Doctoral thesis.

For graduate students holding graduate research assistantships.

Special topics in Industrial and Systems Engineering.

Rigorous introduction to the theory of Beysian Statistical Inference. Bayesian estimation and testing. Conjugate priors. Noninformative priors. Bayesian computation. Bayesian networks and Bayesian signal processing. Various engineering applications.

Analysis of variance, full and fractional factoral designs at two and three levels, orthogonal arrays, response surface methodology, robust parameter design for production/process improvement.

This course is an introduction to constraint programming, from its modeling language to its computational methodology and its applications to scheduling, routing, and resource allocation.

Topics include component reliability and lifetime distributions, hazard rates, system reliability, covariate reliability models, state-dependent models, nonparametric models, statistical estimation and inference, maintenance management and repair processes.

Courses in special topics of timely interest to the profession, conducted by resident or visiting faculty.

Independent research conducted under the guidance of a faculty member.