General Information

Sessions – All sessions will be held in Salon VI at the Georgia Tech Hotel & Conference Center. Each session consists of three 30-minute talks, centered around a specific topic on the uncertainty quantification of complex computational models.

Poster Presentation – Poster presentations are held on Monday from 17:30 – 19:00 in Salon V & VI at the Georgia Tech Hotel & Conference Center. Easels and poster boards are provided at the venue. Please set-up your posters during the break time 15:30-16:00, so that we can start the presentations on-time.

Meals – For all attendees, continental breakfast (near the general session in the second level) and lunch (conference dining room in the first level) is provided on Monday and Tuesday at the Georgia Tech Hotel & Conference Center. A banquet dinner is scheduled on Monday from 19:00 – 21:00 in Conference Room A.


Complete Program Booklet Download

Monday, May 29, 2017

Time Session Event
7:30-8:30   Continental Breakfast
8:30-9:00   Welcome and Opening Remarks

  • Edwin Romeijn (H. Milton Stewart School Chair and Professor, Georgia Tech)
  • C. F. Jeff Wu (Coca-Cola Chair in Engineering Statistics and Professor, Georgia Tech)
9:00-10:30 Session 1 Computer Experiments: Early Work and Recent Developments
Organizer: Peter Qian

  • Michael Stein – University of Chicago Climate Model Emulation and Future Climate Simulation
  • Art Owen – Stanford University On Shapley value for measuring importance of dependent inputs
  • Tom Santner – Ohio State University Challenges in Designing and Using Simulator Experiments in Biomechanics and Biomaterials Research
10:30-11:00   Coffee Break
11:00-12:30 Session 2 Calibration of Models under Uncertainty
Organizer: Matthew Plumlee

  • Daniel Apley – Northwestern University An Empirical Adjustment of the Uncertainty Quantification in Gaussian Process Modeling
  • Oksana Chkrebtii – Ohio State University Advances in discretization uncertainty quantification for differential equation models
  • Rui Tuo – Chinese Academy of Sciences Adjustments to Computer Models via Projected Kernel Calibration
12:30-2:00   Lunch
14:00-15:30 Session 3 Applied Math, Engineering and Computation
Organizer: Dave Higdon

  • Paul Constantine – Colorado School of Mines Active Subspaces: Emerging Ideas for Dimension Reduction in Computational Science and Engineering Models
  • Akil Narayan – University of Utah Sampling strategies for efficient approximations
  • Clayton Webster – ORNL Sparse polynomial approximation for high-dimensional uncertainty quantification
15:30-16:00   Coffee Break
16:00-17:30 Session 4 UQ in Action
Organizer: Ben Haaland

  • Hendrik Hamann – IBM Big data gets physical
  • Johannes Hoetzer – KIT Application of data-science approaches for the analysis of directional solidified ternary alloys
  • Bill Myers – P&G Robust Parameter Design using Computer Experiments
17:30-19:00   Poster Presentation
19:00-21:00   Banquet Dinner



Tuesday, May 30, 2017

Time Session Event
7:30-8:30   Continental Breakfast
8:30-10:00 Session 5 UQ in Emulation, Simulation, and Calibration
Organizer: Roshan Joseph

  • Jim Berger – Duke University
    On Fitting Gaussian Process Emulators
  • Bani Mallick – Texas A&M University
    Bayesian variational approaches for inverse problems
  • Barry Nelson – Northwestern University
    Reducing Simulation Input-Model Risk via Input Model Averaging
10:00-10:30   Coffee Break
10:30-12:00 Session 6 UQ and Model-based Applications
Organizer: Dave Higdon

  • Marc Genton – KAUST Statistics-Based Compression of Global Wind Fields
  • Sez Atamturktur – Clemson University Model Calibration, Validation, and Uncertainty Quantification in Scientific Computing: State-Aware Calibration of Computer Models
  • Salman Habib – ANL The Universe as a Statistical Inverse Problem
12:00-13:30   Lunch
13:30-15:00 Session 7 UQ for Complex Problems
Organizer: Peter Qian

  • Derek Bingham – Simon Fraser University Bayesian model calibration for generalized linear models: An application in radiation transport
  • Antony Overstall – University of Southampton Bayesian Optimal Design for Ordinary Differential Equation Models
  • Peter Marcy – LANL Bayesian Gaussian Process Models on Spaces of Sufficient Dimension Reduction
15:00-15:30   Coffee Break
15:30-17:00 Session 8 Engineering Applications
Organizer: Roshan Joseph

  • Simon Mak – Georgia Tech Physics-based modeling of large-eddy simulations for rocket injectors
  • Matthew Plumlee – University of Michigan Bayesian calibration of inexact computer models
  • Peter Qian – University of Wisconsin Invariance-Preserving Emulation for Computer Models, with Application to Structural Energy Prediction
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