Organizing Committee
Abstract

Mathematical models of scientific applications often involve simulations with a large number of degrees of freedom that strain even the most efficient of algorithms. A clear need is the rigorous development of models with reduced complexity that retain fidelity to the application. Mathematics-based reduced-order modeling applies techniques in nonlinear approximation, projection-based discretizations, sparse surrogate construction, and high-dimensional approximation, in order to construct a model surrogate with near-optimal approximation properties. This workshop focuses on theoretical and algorithmic advances in mathematics-based model order reduction of various types: reduced basis methods, projection-based methods for dynamical systems, and sparse and low-rank approximations in high dimensions.

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Confirmed Speakers & Participants

Talks will be presented virtually or in-person as indicated in the schedule below.

  • Speaker
  • Poster Presenter
  • Attendee
  • Virtual Attendee

Workshop Schedule

Monday, February 17, 2020
TimeEventLocationMaterials
8:30 - 8:55am ESTRegistration - ICERM 121 South Main Street, Providence RI 0290311th Floor Collaborative Space 
8:55 - 9:00am ESTWelcome - ICERM Director11th Floor Lecture Hall 
9:00 - 9:45am ESTFurther exploitation of the RB framework - Yvon Maday, Sorbonne Université11th Floor Lecture Hall
10:00 - 10:30am ESTCoffee/Tea Break11th Floor Collaborative Space 
10:30 - 11:15am ESTAdaptivity concepts for POD reduced-order modeling - Carmen Gräßle, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg11th Floor Lecture Hall
11:30 - 12:15pm ESTSampling low-dimensional Markovian dynamics for learning certified reduced models from data - Benjamin Peherstorfer, Courant Institute, New York University11th Floor Lecture Hall
12:30 - 2:30pm ESTBreak for Lunch / Free Time  
2:30 - 3:15pm ESTReduced Models in State Estimation - Wolfgang Dahmen, University of South Carolina11th Floor Lecture Hall
3:30 - 4:00pm ESTCoffee/Tea Break11th Floor Collaborate Space 
4:00 - 4:45pm ESTLinear and nonlinear methods for model reduction - Diane Guignard, Texas A&M University11th Floor Lecture Hall
5:00 - 6:30pm ESTWelcome Reception11th Floor Collaborative Space 
Tuesday, February 18, 2020
TimeEventLocationMaterials
9:00 - 9:45am ESTThe Loewner framework for model reduction of large-scale systems - Athanasios Antoulas, Rice University11th Floor Lecture Hall
10:00 - 10:30am ESTCoffee/Tea Break11th Floor Collaborative Space 
10:30 - 11:15am ESTModel Order Reduction for Higher Order Systems - Heike Fassbender, TU Braunschweig11th Floor Lecture Hall
11:30 - 12:15pm ESTEmbedding properties of data-driven dissipative reduced order models - Vladimir Druskin, WPI11th Floor Lecture Hall
12:30 - 2:00pm ESTBreak for Lunch / Free Time  
2:00 - 2:45pm ESTOperator inference for non-intrusive model reduction of non-polynomial nonlinear systems - Boris Kramer, University of California San Diego11th Floor Lecture Hall
3:00 - 3:45pm ESTThe Loewner Framework for Model Reduction of Flow Equations - Matthias Heinkenschloss, Rice University11th Floor Lecture Hall
4:00 - 4:20pm ESTPoster Session Blitz11th Floor Lecture Hall 
4:30 - 6:30pm ESTMathematics of Reduced Order Models Poster Session11th Floor Collaborate Space
Wednesday, February 19, 2020
TimeEventLocationMaterials
9:00 - 9:45am ESTStructure-preserving dynamical reduced order models for Hamiltonian systems - Cecilia Pagliantini, EPFL, Lausanne, Switzerland11th Floor Lecture Hall
10:00 - 10:30am ESTCoffee/Tea Break11th Floor Collaborative Space 
10:30 - 11:15am ESTReduced Basis Methods for the Wave Equation - Silke Glas, Cornell University11th Floor Lecture Hall
11:30 - 12:15pm ESTParametrized Partial Differential Equations and Back-of-the-Envelope Calculations - Anthony Patera, MIT11th Floor Lecture Hall
12:30 - 12:40pm ESTGroup Photo11th Floor Lecture Hall 
12:40 - 2:30pm ESTBreak for Lunch / Free Time  
2:30 - 3:15pm ESTA reduced basis method for parametrized variational inequalities applied to contact mechanics - Amina Benaceur, MIT11th Floor Lecture Hall
3:30 - 4:00pm ESTCoffee/Tea Break11th Floor Collaborate Space 
4:00 - 4:45pm ESTClosed-loop controls for fluids - Jeff Borggaard, Virginia Tech11th Floor Lecture Hall,
Thursday, February 20, 2020
TimeEventLocationMaterials
9:00 - 9:45am ESTPredictive data science for physical systems- From model reduction to scientific machine learning - Karen Willcox, Oden Institute for Computational Engineering and Sciences11th Floor Lecture Hall
10:00 - 10:30am ESTCoffee/Tea Break11th Floor Collaborative Space 
10:30 - 11:15am ESTData-driven Modeling and Optimization of Dissipative Dynamics - Christopher Beattie, Virginia Tech11th Floor Lecture Hall
11:30 - 12:15pm ESTModel reduction for port-Hamiltonian differential-algebraic systems - Volker Mehrmann, TU Berlin11th Floor Lecture Hall
12:30 - 2:30pm ESTBreak for Lunch / Free Time  
2:30 - 3:15pm ESTAutomatic Generation of Minimal and Reduced Models for Structured Parametric Dynamical Systems - Igor Pontes Duff, Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany11th Floor Lecture Hall
3:30 - 4:00pm ESTCoffee/Tea Break11th Floor Collaborate Space 
4:00 - 4:45pm ESTA Rank-Minimization Approach to Learning Dynamical Systems from Frequency Response Data - Pawan Goyal, Max Planck Institute, Magdeburg, Germany11th Floor Lecture Hall
Friday, February 21, 2020
TimeEventLocationMaterials
9:00 - 9:45am ESTConvolutional autoencoders and LSTMs - using deep learning to overcome Kolmogorov-width limitations and accurately model errors in nonlinear model reduction - Kevin Carlberg, University of Washington11th Floor Lecture Hall
10:00 - 10:30am ESTCoffee/Tea Break11th Floor Collaborative Space 
10:30 - 11:15am ESTModel order reduction of parametric transport-dominated problems in Wasserstein spaces (joint work with D. Lombardi, O. Mula, F.-X. Vialard) - Virginie Ehrlacher, CERMICS – ENPC11th Floor Lecture Hall
11:30 - 12:15pm ESTH2-Optimal Model Reduction Using Projected Nonlinear Least Squares - Jeffrey Hokanson, University of Colorado Boulder11th Floor Lecture Hall
12:30 - 2:30pm ESTBreak for Lunch / Free Time  
3:30 - 4:00pm ESTCoffee/Tea Break11th Floor Collaborate Space 

Associated Semester Workshops

Lecture Videos

H2-Optimal Model Reduction Using Projected Nonlinear Least Squares

Jeffrey Hokanson
University of Colorado Boulder
February 21, 2020
Mathematics of Reduced Order Models
Play

Convolutional autoencoders and LSTMs - using deep learning to overcome Kolmogorov-width limitations and accurately model errors in nonlinear model reduction

Kevin Carlberg
University of Washington
February 21, 2020
Mathematics of Reduced Order Models
Play     Abstract

A Rank-Minimization Approach to Learning Dynamical Systems from Frequency Response Data

Pawan Goyal
MPI Magdeburg
February 20, 2020
Mathematics of Reduced Order Models
Play     Abstract

Automatic Generation of Minimal and Reduced Models for Structured Parametric Dynamical Systems

Igor Pontes Duff
Max Planck Institute for Dynamics of Complex Technical Systems
February 20, 2020
Mathematics of Reduced Order Models
Play     Abstract

Model reduction for port-Hamiltonian differential-algebraic systems

Volker Mehrmann
TU Berlin
February 20, 2020
Mathematics of Reduced Order Models
Play     Abstract     Slides

Data-driven Modeling and Optimization of Dissipative Dynamics

Christopher Beattie
Virginia Tech
February 20, 2020
Mathematics of Reduced Order Models
Play     Abstract

Predictive data science for physical systems- From model reduction to scientific machine learning

Karen Willcox
UT Austin
February 20, 2020
Mathematics of Reduced Order Models
Play     Abstract     Slides

Closed-loop controls for fluids

Jeff Borggaard
Virginia Tech
February 19, 2020
Mathematics of Reduced Order Models
Play     Slides

A reduced basis method for parametrized variational inequalities applied to contact mechanics

Amina Benaceur
MIT
February 19, 2020
Mathematics of Reduced Order Models
Play     Abstract     Slides

The Loewner Framework for Model Reduction of Flow Equations

Matthias Heinkenschloss
Rice University
February 18, 2020
Mathematics of Reduced Order Models
Play     Abstract     Slides

Operator inference for non-intrusive model reduction of non-polynomial nonlinear systems

Boris Krämer
University of California San Diego
February 18, 2020
Mathematics of Reduced Order Models
Play     Abstract     Slides

Embedding properties of data-driven dissipative reduced order models

Vladimir Druskin
Worcester Polytechnic Institute
February 18, 2020
Mathematics of Reduced Order Models
Play     Abstract     Slides

The Loewner framework for model reduction of large-scale systems

Thanos Antoulas
Rice University
February 18, 2020
Mathematics of Reduced Order Models
Play     Abstract     Slides

Linear and nonlinear methods for model reduction

Diane Guignard
Texas A&M University
February 17, 2020
Mathematics of Reduced Order Models
Play     Abstract

Reduced Models in State Estimation

Wolfgang Dahmen
University of South Carolina
February 17, 2020
Mathematics of Reduced Order Models
Play     Abstract

Sampling low-dimensional Markovian dynamics for learning certified reduced models from data

Benjamin Peherstorfer
Courant Institute, New York University
February 17, 2020
Mathematics of Reduced Order Models
Play     Abstract     Slides

Adaptivity concepts for POD reduced-order modeling

Carmen Gräßle
Max Planck Institute for Dynamics of Complex Technical Systems
February 17, 2020
Mathematics of Reduced Order Models
Play     Abstract     Slides

Further exploitation of the RB framework

Yvon Maday
Sorbonne Université
February 17, 2020
Mathematics of Reduced Order Models
Play