nanoHUB.org - Courses: Introduction to Uncertainty Quantification: Offerings

Home › Courses › Introduction to Uncertainty Quantification › Offerings

Courses

Introduction to Uncertainty Quantification

The objective of this summer school on Uncertainty Quantification and its Applications is to present an accessible introduction to the basic tools of uncertainty quantification, with the goal of orienting attendees to the field and helping them address UQ questions in their application areas of interest. Lectures will provide basic introductions to probability and stochastic processes, data analysis, estimation and inference, sensitivity analysis, uncertainty propagation, sampling methods, Bayesian computation, experimental design, and model validation. In addition, several guest lecturers will present a diverse set of applications and snapshots of current research, in which uncertainty quantification plays an important role.

Offering	Enrolled	Enrollment
2015 Summer School	Enroll in Course	Accepting

Enrolled:	150

Preview course

About the Instructors

Alejandro Strachan

Purdue University

Alejandro Strachan is a Professor of Materials Engineering at Purdue University and the Deputy Director of the Purdue’s Center for Predictive Materials and Devices (c-PRIMED). He leads the efforts on uncertainty quantification and materials NSF’s Network for Computational Nanotechnology. Before joining Purdue, he was a Staff Member in the Theoretical Division of Los Alamos National Laboratory and worked as a Postdoctoral Scholar and Scientist at Caltech. He received a Ph.D. in Physics from the University of Buenos Aires, Argentina, in 1999. Among other recognitions, Prof. Strachan was named a Purdue University Faculty Scholar (2012-2017), received the Early Career Faculty Fellow Award from TMS in 2009 and the Schuhmann Best Undergraduate Teacher Award from the School of Materials Engineering, Purdue University in 2007. Prof. Strachan’s research focuses on the development of predictive atomistic and molecular simulation methodologies to describe materials from first principles, their application to problems of technological importance and quantification of associated uncertainties. Application areas of interest include: coupled electronic, chemical and thermo-mechanical processes in devices of interest for nanoelectronics and energy as well as polymers and their composites, molecular solids and active materials, including shape memory and high-energy density materials. His research has resulted in over 95 peer reviewed journal publications. [http://scholar.google.com/citations?user=JOeDlUkAAAAJ Publication list.]

Ralph Smith

North Carolina State University

Ralph Smith is a Distinguished Professor of Mathematics in the North Carolina State University Department of Mathematics, Associate Director of the Center for Research in Scientific Computing (CRSC), and a member of the Operations Research Program.

Kevin F Garrity

National Institute of Standards and Technology

This instructor has yet to write their bio.

Ilias Bilionis

Purdue University

Dr. Ilias Bilionis is an Assistant Professor at the School of Mechanical Engineering, Purdue University. His research is motivated by energy and material science applications and it focuses on the development of generic methodologies for design and optimization under uncertainty, reliability analysis, model calibration and learning models out of data. Prior to his appointment at Purdue he was a Postdoctoral Researcher at the Mathematics and Computer Science Division (MCS), Argonne National Laboratory. He received his PhD in Applied Mathematics from Cornell University in 2013 and his Diploma in Applied Mathematics from the National Technical University of Athens in 2008.

Introduction to Uncertainty Quantification

Other courses by these instructors

nanoHUB-U: From Atoms to Materials: Predictive Theory and Simulations

MSE 270: Atomistic Materials Science

EAFIT-Purdue: online simulations in engineering and science education