Summer School on Mathematical and Statistical Model Uncertainty

SAMSI and CANSSI logos
KEY logos


Dates: July 23-July 27, 2018.

The emerging area of uncertainty quantification (UQ) for computer models is the focus of the 2018-2019: Program Model Uncertainty: Mathematical and Statistical (MUMS) at the Statistical and Applied Mathematical Sciences Institute (SAMSI). The aim of the SAMSI 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. To this end, the Canadian Statistical Sciences Institute (CANSSI) and SAMSI are jointly sponsoring the Summer School on UQ.

The objective of this 5-day summer school is to present the statistical and mathematical foundations for UQ in a wide variety of applications. Among the many challenges include understanding all of the sources of variability (statistical and mathematical) and combining models and data to make inferences about physical systems, or the parameters that govern them. The approach will be one where attendees will learn UQ methods by implementation and where roughly half of the time will be spent on problem solving (exercises and the real-world problem). We also aim to establish a common nomenclature among the mathematical and statistical sciences communities.

The target audience for the summer school is graduate students and post-docs interested in learning about UQ. Senior level undergraduate students are also welcome, particularly those who have interest, or experience, in UQ and also implementing new methods (i.e., you should know some computing).

Note: Summer School participants do NOT have to be involved in the SAMSI program.


Derek Bingham, Department of Statistics and Actuarial Science, Simon Fraser University

Paul Constantine , Department of Computer Science, University of Colorado, Boulder


The summer school will be hosted at the Big Data Hub on the Simon Fraser University (SFU) main campus. Summer school presentations will be held in the Presentation Studio at SFU’s Big Data Hub, and workspace will be provided in 2-4 flexible meeting spaces.


Derek Bingham Simon Fraser University
Paul Constantine University of Colorado, Boulder
Leanna House Virginia Tech
Dave Higdon Social Decisions Analytics Lab, Virginia Tech


We aim to have the first half of each day consist of presentations and lectures and the second half of the day consist of work on activities, worksheets, numerical experiments and coding. We will take great care to properly distinguish between applied problems, concepts and methods. It is essential to first formulate the problem(s) and then to discuss/compare different potential approaches – with emphasis on those that will be explored in the SAMSI program. Participants will gain hands-on experience using new and existing code for cutting edge techniques. Likely coding environments are Matlab, Python and R. The summer school participants will be introduced to a real research problem.

Things to do before arriving

While not mandatory, having your own laptop available will be a good idea. It is also good to have at least one of the following programming environments installed: R, Matlab or Python. We will have local wifi passwords avaialble and eduroam for internet connectivity. If you are not bringing a laptop, do not worry because there are computing resources avaiable.




Getting to the hotels

There are several ways to get to the hotels. The most environmentally friendly way to do so is to take the Skytrain from the airport to Lougheed Station. It should take about an hour and the hotels are a short walk from the station.

Getting to the summer school

There are two hotels for the workshop - Best Western Coquitlam and the Exective Plaza, Coquitlam. A shuttle bus will pick up at each hotel and return you to the hotel following the workshop.

Best Western Executive Plaza
Pick up time 7:50 8:10
If you miss the bus, all is not lost! The Lougheed Mall Skyrain Staion is a short walk from the hotels. Take the Skytrain (you will have to pay) from Lougheed one stop to the Production Way Station. The 145 bus will take you to the University. The Big Data Hub can be found here: Location of Big Data Hub


Please contact Derek Bingham if you have any questions.