Texas A&M University Institute for Scientific Computation

Description

Data-driven modeling is a cornerstone for many applications. Finding appropriate scale-level models conditioned to the data requires some type of reduced-order modeling. This workshop brings together experts working on mathematical, statistical, computational, and engineering aspects of model reduction to share their research experience.

The workshop will be hosted by Texas A&M University in College Station, Texas, and is supported by the Institute for Scientific Computation.

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Registration

There is no registration required to participate in this workshop. Participants may come and go as they please.

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Organizing Committee

 

Speakers

Suman Chakravort,

Department of Aerospace Engineering
A Reduced Order Iterative Linear Quadratic Regulator (ILQR) Technique for the Optimal Control of Nonlinear Partial Differential Equations

Paul Cizmas, 

Department of Aerospace Engineering
A POD-Based Reduced-Order Model for Turbomachinery Flows

Yalchin Efendiev,

Department of Mathematics
Multicontinuum Homogenization as a Model Reduction Technique

Yusuf Falola,

Harold Vance Department of Petroleum Engineering
Neural Operator-Based Rapid Forecast of CO2 Pressure and Saturation Distribution During Geological Carbon Storage

Eduardo Gildin,

Harold Vance Department of Petroleum Engineering
Model Reduction for Reservoir Simulation at the Crossroads: Is it Feasible to Construct an Input-Output Invariant Proxy Model?

David Gutman,

Wm Michael Barnes Department of Industrial & Systems Engineering
Tangent Subspace Descent on Quotient Manifolds

Joseph Kwon, 

Artie McFerrin Department of Chemical Engineering
Transformer-based Hybrid Modeling and Control of Evolving, Nonlinear Processes

Jaesung Lee, 

Wm Michael Barnes Department of Industrial & Systems Engineering
Statistical Modeling of Random Shifting and Shapes in Functional Data and Uncertainty Quantification via Landmark-Embedded Hierarchical Gaussian Processes

Matthias Maier,

Department of Mathematics
Homogenization of Layered Heterostructures

Arash Noshadravan,

Zachry Department of Civil & Environmental Engineering
Model Reduction for Simplifying Thermal Efficiency Planning at City Scale

Jean Ragusa, 

Department of Nuclear Engineering
Model-Order Reduction for Neutron Transport in the Atmosphere

Rui Tuo, 

Wm Michael Barnes Department of Industrial & Systems Engineering
Scalable Algorithms for Gaussian Process Regression via Kernel Packets

Rami Younis, 

Harold Vance Department of Petroleum Engineering
Two Cases of Leveraging Solution Character to Expedite Computation
Schedule

All workshop presentations will take place in Joe C. Richardson Petroleum Engineering Building (RICH) 910. Please note that the schedule is tentative and subject to change. All times listed are local time.

–
Welcome
–
Yalchin Efendiev, Department of Mathematics
Multicontinuum Homogenization as a Model Reduction Technique
–
Jaesung Lee, Wm Michael Barnes Department of Industrial & Systems Engineering
Statistical Modeling of Random Shifting and Shapes in Functional Data and Uncertainty Quantification via Landmark-Embedded Hierarchical Gaussian Processes
–
Yusuf Falola, Harold Vance Department of Petroleum Engineering
Neural Operator-Based Rapid Forecast of CO2 Pressure and Saturation Distribution During Geological Carbon Storage
–
Break
–
David Gutman, Wm Michael Barnes Department of Industrial & Systems Engineering
Tangent Subspace Descent on Quotient Manifolds
–
Joseph Kwon, Artie McFerrin Department of Chemical Engineering
Transformer-based Hybrid Modeling and Control of Evolving, Nonlinear Processes
–
Arash Noshadravan, Zachry Department of Civil & Environmental Engineering
Model Reduction for Simplifying Thermal Efficiency Planning at City Scale
–
Matthias Maier, Department of Mathematics
Homogenization of Layered Heterostructures
–
Lunch
–
Suman Chakravorty, Department of Aerospace Engineering
A Reduced Order Iterative Linear Quadratic Regulator (ILQR) Technique for the Optimal Control of Nonlinear Partial Differential Equations
–
Eduardo Gildin, Harold Vance Department of Petroleum Engineering
Model Reduction for Reservoir Simulation at the Crossroads: Is it Feasible to Construct an Input-Output Invariant Proxy Model?
–
Rui Tuo, Wm Michael Barnes Department of Industrial & Systems Engineering
Scalable Algorithms for Gaussian Process Regression via Kernel Packets
–
Break
–
Paul Cizmas, Department of Aerospace Engineering
A POD-Based Reduced-Order Model for Turbomachinery Flows
–
Rami Younis, Harold Vance Department of Petroleum Engineering
Two Cases of Leveraging Solution Character to Expedite Computation
–
Jean Ragusa, Department of Nuclear Engineering
Model-Order Reduction for Neutron Transport in the Atmosphere
–
Closing Remarks

Contact Information

If you have any questions concerning this workshop, email Brad Shumbera at shumbera@tamu.edu.