AMCS 390 Course:
Bayesian Analysis of Stochastic
Process Models
Led by Dr. Fabrizio Ruggeri
March 25 – April 24
Sat and Wed from 3:00 – 4:30 p.m. and
Mon from 10:30 a.m. – 12:00 p.m.
Engineering Science Hall, room 2132
Students will be introduced to Bayesian modeling in selected, but relevant, stochastic processes and their applications: Markov chains, Poisson processes, reliability and queues. Students will be asked to analyze real data, from the elicitation of priors and modeling to (numerical) computation of estimates and forecasts and interpretation of findings.
For more information contact: Raul.Tempone@kaust.edu.sa or marialeticia.garciapozzi@kaust.edu.sa
Sponsored by SRI – Center for Uncertainty Quantification