CANSSI/SAMSI Summer School on Mathematical and Statistical Model Uncertainty
The Canadian Statistical Sciences Institute (CANSSI) and the Statistical and Applied Mathematical Sciences Institute (SAMSI) are jointly sponsoring the Summer School on uncertainty quantification (UQ). The area of UQ for computer models is the focus of the 2018-2019 SAMSI program on Model Uncertainty: Mathematical and Statistical (MUMS). The aim of the program is to bring together statistical and mathematical scientists to tackle important common research problems in UQ and to train the next generation of UQ researchers.
The summer school will be held at Simon Fraser University, July 23-July 27, 2018.
Participants will receive an overview of cutting edge methods and applications of UQ such as how to formulate UQ problems, theoretical basis for uncertainty, computer model emulation and calibration, and sensitivity analysis. Additionally, participants will gain hands-on experience using code for cutting edge techniques (e.g., Bayesian computer model calibration).
The main lecturers are:
Derek Bingham, Simon Fraser University
Paul Constantine, University of Colorado, Boulder
Leanna House, Virginia Tech
Dave Higdon, Social Decisions Analytics Lab, Virginia Tech
Participants must apply to attend the summer school. Please follow the following link for details: http://people.stat.sfu.ca/~dbingham/summer-school/
Participants are expected to arrive for the summer school on Sunday, July 22, 2011 and remain in continuous attendance until Friday, July 27, 2011.
Our aim is to provide lodging for all out of town participants. Spaces are limited, so please apply as soon as possible.
Applications will be processed in a first come, first served basis. To be considered for lodging, please make sure to apply before May 31, 2018. Applications will be considered past May 31, but you may be on your own for finding a place to stay.
General inquiries about the summer school can be sent to email@example.com.