Events & Updates

April 2022
Various AEOLUS team members will be attending and presenting at the SIAM Conference on Uncertainty Quantification (UQ22). Karen Willcox and Youssef Marzouk will be giving plenary talks.
March 2022
The BNL/TAMU team's transfer learning error estimation work supported by AEOLUS has been featured in ACM Tech News as well as on the DOE website.
Karen Willcox is delivering an Invited Keynote Talk "Mathematical and Computational Foundations for Enabling Predictive Digital Twins at Scale" at SupercomputingAsia 2022 (SCA22).
DeWitt is organizing the "ICME Case Studies: Successes and Challenges for Generation, Distribution, and Use of Public/Pre-Existing Materials Datasets" at the 2022 TMS Annual Meeting.
February 2022
Karen Willcox has been elected to the National Academy of Engineering (NAE) for 2022. The corresponding announcement can be found here.
January 2022
Chen gave the invited talk “Fast and scalable computational methods for learning and optimization under uncertainty”, Georgia Tech.
Karen Willcox is delivering the AIAA Structures, Structural Dynamics, and Materials (SDM) Lecture "From reduced-order modeling to scientific machine learning: How computational science is enabling the design of next-generation aerospace systems." The lecture will be presented at the AIAA Scitech Forum on January 5, 2022.
Karen Willcox is an Invited Panelist for "Do we still need physics-based models?", a panel as part of the Roger Sargent Lecture at Imperial College London.
December 2021
Chen gave the invited talk “Fast and scalable computational methods for learning and optimization under uncertainty”, East China Normal University.
November 2021
Chen gave the invited talk “Dimension reduction for Bayesian inference”, Seminar for Applied Mathematics, ETH Zurich.
October 2021
Ghattas gave the invited plenary talk, “Parsimonious structure-exploiting deep neural network surrogates for Bayesian inverse problems,” at MATHIAS 2021, Paris, France.
Ghattas gave the invited talk “Derivative-informed projected neural networks for high-dimensional parametric maps governed by PDEs” at the RICAM Hybrid Prequel Workshop on Tomography Across the Scales, Johann Radon Institute (RICAM), Austrian Academy of Sciences, Linz, Austria.
Ghattas gave the invited Colloquium “Parsimonious structure-exploiting deep neural network surrogates for Bayesian inverse problems” at the Max Planck Institute for Dynamics of Complex Technical Systems, Magdeburg, Germany.
September 2021
AEOLUS is a co-sponsor of the 2021 New York Scientific Data Summit. Frank Alexander and Omar Ghattas are on the organizing committee.
Willcox is giving an invited plenary talk “Engineering Design in the Age of Big Data and Big Compute” at the NAFEMS World Congress.
AEOLUS PI Karen Willcox is co-chairing the 2022 SIAM Conference on the Mathematics of Data Science, to be held September 2022.
Qian gave the invited talk “Bayesian active learning by objective-oriented uncertainty quan-tification,” at the International Workshop on Signal and Information Intelligent Learning & Processing (SIILP)
July 2021
AEOLUS team members organized multiple minisymposia at the 16th U.S. National Congress on Computational Mechanics
Ghattas is giving a plenary talk “Parsimonious structure-exploiting deep neural network surrogates for Bayesian inverse problems,” at the US National Congress on Computational Mechanics (USNCCM) 2021.
Chen gave the invited talk “Stein Variational Reduced Basis Bayesian Inversion”, SIAM-AN21, (online).
Chen gave the invited talk “Bayesian learning of heterogeneous epidemic models”, USNCCM16.
May 2021
Ghattas gave the invited seminar “Parsimonious structure-exploiting deep neural network surrogates for Bayesian inverse problems at the Geophysical Fluid Dynamics Laboratory, Princeton, NJ.
Burkovska gave an invited presentation at the 50th Barrett Memorial Lectures, Approximation, Applications, and Analysis of Nonlinear Nonlocal Models at the University of Tennessee entitled "Nonlocal phase-field models permitting sharp interfaces"
Qian gave a short course on introductory machine learning in the iDiscovery Workshop on Data Science Foundations and Computational Practice, Texas A&M Institute of Data Science.
April 2021
Chen gave the invited talk “Fast and scalable computational methods for learning and optimization under uncertainty”, Xi’an Jiaotong University.
Chen gave the invited talk “Projected Variational Methods for High-dimensional Bayesian Inference”, SCAN Seminar, Cornell University.
March 2021
AEOLUS team members organized multiple minisymposia at the 2021 SIAM Conference on Computational Science & Engineering.
Willcox is giving an invited plenary talk “A Probabilistic Graphical Model Foundation for Predictive Digital Twins” at the SIAM Conference on Computational Science and Engineering (CSE21)
Chen gave the invited talk “Stein variational methods for Bayesian optimal experimental design”, SIAM Conference on Computational Science & Engineering (CSE21).
Chen gave the invited talk “Taylor Approximation for Chance Constrained Optimization”, SIAM Conference on Computational Science & Engineering (CSE21).
February 2021
Chen gave the invited talk “Taylor approximation for PDE and chance constrained optimization under uncertainty”, BIRS Workshop: Optimization under Uncertainty: Learning and Decision Making.
January 2021
Oden is giving an invited talk “Phase field models of the growth of tumors embedded in an evolving vascular network: Dynamic 1D-3D models of angiogenesis” at the VII Workshop on Mathematical and Computational Modeling of Tumor Growth.
November 2020
Webster is giving an invited short course “Uncertainty quantification and approximation theory for parameterized PDEs” at the School of Mathematics, African Institute for Mathematical Sciences (AIMS), Cape Town, South Africa.
Stephen DeWitt, Bala Radhakrishnan, Yuanxun Bao, Yigong Qin, George Biros, Jean-Luc Fattebert, and John Turner, “Phase Field Modeling of AM Solidification Microstructure with Algorithmic Feature Extraction to Facilitate Reduced Order Model Development”, MS&T 2020 (Virtual)
Ghattas gave the invited seminar “Parsimonious structure-exploiting deep neural network surrogates for Bayesian inverse problems” at the MOX Colloquia, Modeling and Scientific Computing Lab, Department of Mathematics, Politecnico di Milano, Italy
October 2020
Ghattas and Willcox are giving invited keynote talks at the Opening Conference, NSF Institute for Mathematical and Statistical Innovation, University of Chicago, October 7--9, 2020.
Frank Alexander, Omar Ghattas and Karen Willcox are part of the Planning Committee for the New York Scientific Data Summit 2020
Ghattas gave the invited talk “Parsimonious structure-exploiting deep neural network surrogates for Bayesian inverse problems” at the Robert J. Melosh Medal Competition for Best Student Paper in Finite Elements, Duke University, Durham, NC
September 2020
Ghattas gave the invited talk “Parsimonious structure-exploiting deep neural network surrogates for Bayesian inverse problems” at the Society for Engineering Science, 2020 Virtual Technical Meeting
Chen gave the invited talk “Projected Stein variational methods for high-dimensional Bayesian inference.” University of California, Los Angeles.
August 2020
Willcox, K. - “Toward predictive digital twins: From physics-based modeling to scientific machine learning.“ Opening Keynote, ASME Design Automation Conference, August 2020.
July 2020
Willcox, K. - “Predictive digital twins: Where data-driven learning meets physics-based modeling“. Keynote talk for JuliaCon.
Willcox, K. - “Toward predictive digital twins: Component-based adaptive reduced-order models and interpretable machine learning“. Invited Plenary Talk. World Congress on Computational Mechanics (WCCM). (This conference was cancelled.)
June 2020
Ghattas and Marzouk are co-organizing the Workshop on Mathematical Foundations of Data Assimilation and Inverse Problems, at the Conference on Foundations of Computational Mathematics (FoCM’20), Vancouver, Canada, June 15-24, 2020.
The Willcox Group released an Operator Inference model reduction package with tutorial examples. https://github.com/Willcox-Research-Group/rom-operator-inference-Python3
April 2020
Paper Multifidelity Monte Carlo estimation of variance and sensitivity indices received 2020 SIAM Student Paper Prize. Research was conducted under previous MMICC center (collaboration between Willcox Group and LANL).
Marzouk is co-organizer of the Oberwolfach workshop on “Data assimilation: mathematical foundations and applications.“
March 2020
Marzouk is giving an invited plenary talk at the 2020 SIAM Conference on Uncertainty Quantification (UQ20) in Munich, Germany.
Chen is giving an invited talk “Projected Stein variational methods for high-dimensional Bayesian inference” at the 2020 SIAM Conference on Uncertainty Quantification (UQ20) in Munich, Germany.
January 2020
Webster is named Editor-in-Chief, Numerical Methods for Partial Differential Equations.
Ghattas is co-organizing the Workshop on Mathematical Modeling in Glaciology at the Banff International Research Station, Banff, Canada, January 12–17, 2020.
Ghattas gave the invited seminar “Machine Learning for Inferring Scientific Models: Hope or Hype?” at Shell, Houston, TX.
December 2019
Marzouk is co-organizing the MIT/Alan Turing Institute/Lloyd’s Register Foundation workshop on Data-Centric Engineering, to be held Dec 9-12 in Cambridge, MA. Ghattas and Willcox are giving invited talks at the workshop.
Chen is presenting an invited poster “Projected Stein variational Newton: A fast and scalable Bayesian inference method in high dimensions” at the Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada.
November 2019
Predictive data science: From model reduction to scientific machine learning. Invited Keynote Talk, SC19, Denver, CO.
Ghattas is co-organizing the Workshop on Big Data, Data Assimilation, and Uncertainty Quantification as part of the Trimester on Mathematics of Climate and the Environment, Institut Henri Poincare, Paris, France, November 12-15, 2019. Ghattas is co-teaching the mini-course “Big data, data assimilation, and uncertainty quantification” immediately preceding the workshop.
Chen is giving an invited talk “Projected Stein variational Newton: A fast and scalable Bayesian inference method in high dimensions” at the Workshop on Optimization and Inversion under Uncertainty, November 11-15, 2019, in Linz, Austria.
October 2019
AEOLUS co-PI Biros gives two invited talks at the European Numerical Mathematics and Advanced Applications Conference The first talk is " PDE-constrained optimization for importance sampling of rare events"; and the second talk is "Reduced order models for the simulation of microfluidic devices for biological fluids
Marzouk gives an invited lecture at RWTH Aachen University.
Webster delivering short course on Uncertainty quantification and approximation theory for parameterized PDEs, School of Mathematics , African Institute for Mathematical Sciences (AIMS), Cape Town, South Africa.
Willcox is giving an Invited Keynote Talk "Towards efficient multifidelity modeling for engineering design under uncertainty: From model reduction to scientific machine learning" at the European Numerical Mathematics and Advanced Applications Conference, Egmond aan Zee, The Netherlands.
September 2019
AEOLUS co-PI Clayton Webster served as the Organizing Chair of The 2019 SIAM SEAS Annual Conference; The University of Tennessee, Knoxville, TN. Conference website: https://www.math.utk.edu/SIAM-SEAS/
AEOLUS co-PI Clayton Webster served on the Scientific Committee of The 8th workshop on high-dimensional approximation; Seminar for Applied Mathematics, ETH Zurich, Zurich, Switzerland. https://www.math.ethz.ch/sam/news-and-events/conferences-and-workshops/8th-workshop-on-high-dimensional-approximation.html
AEOLUS co-PI Tinsley Oden gave an invited Keynote lecture to Annual Meeting and Summer School 2019 ; IRTG 2379 in Austin on "Phase-Field Models of Phase Change of Complex Systems : Block Copolymers and Growth of VascularTumors", July , 2019.
AEOLUS co-PI Tinsley Oden gave the Keynote lecture at cellMath, a workshop on tumor growth modeling held at the Technical University of Munich (TUM) on September 10, 2019, on "A Review of Multiscale Models of Tumor Growth".
AEOLUS co-PI Biros gives invited talk titled "Machine learning-accelerated simulations of complex fluids", at the 10th International Workshop on Meshfree Methods for Partial Differential Equations
A dedication ceremony was held for the NSF-supported Frontera supercomputer at UT Austin’s Texas Advanced Computing Center. Ghattas is Chief Scientist, and George Biros and Robert Moser are on the Science Team, for this project. The nearly 50 petaflops Frontera is the fastest university-based supercomputer in the world, and 5th fastest overall.
Marzouk is an invited lecturer at the MASCOT-NUM Research School on Uncertainty in Scientific Computing, 23–27 September 2019. Fréjus, France.
Willcox is giving the Kalman Lecture on "Predictive data science for physical systems: From model reduction to scientific machine learning" at the University of Potsdam, Germany, September 2019.
Chen is one main lecturer in the Cargese summer school on "The Mathematics for Climate and Environment", Cargese, France http://www.geosciences.ens.fr/CliMathParis2019_Cargese/index.html
August 2019
AEOLUS co-PI Robert Moser gives invited talk titled “Uncertainty, Validation and Prediction with Computational Models” at 1st Computational Physics School for Fusion Research (https://sites.google.com/view/mit-psfc-cps-fr2019/home), CPS-FR 2019.
AEOLUS co-PI Marzouk gave an invited talk titled “Bayesian modeling and computation for inverse problems” at 1st Computational Physics School for Fusion Research (https://sites.google.com/view/mit-psfc-cps-fr2019/home), CPS-FR 2019.
AEOLUS co-PI Robert Moser gives invited talk titled “Uncertainty, Validation and Prediction with Computational Models” at 1st Computational Physics School for Fusion Research (https://sites.google.com/view/mit-psfc-cps-fr2019/home), CPS-FR 2019.
July 2019
AEOLUS co-director Karen Willcox is giving the opening plenary talk on "From nonlinear partial differential equations to low-dimensional models: Physics-based model reduction" at the 15th U.S. National Congress on Computational Mechanics
AEOLUS co-director Omar Ghattas is giving an invited talk on "Large-scale stochastic PDE-constrained optimization" at the International Congress on Industrial and Applied Mathematics
Watch a video interview with AEOLUS co-director Omar Ghattas on large-scale stochastic PDE-constrained optimization.
AEOLUS co-director Karen Willcox is giving an invited talk on "Predictive data science for physical systems: From model reduction to scientific machine learning" at the International Congress on Industrial and Applied Mathematics
Watch a video interview with AEOLUS co-director Karen Willcox on predictive data science.
AEOLUS co-PI George Biros gave an invited talk on "BIMC: The Bayesian Inverse Monte Carlo method for goal-oriented uncertainty quantification", at the Applied Inverse Conference 2019
Ghattas gave an invited talk entitled “Fast methods for Bayesian inverse problems governed by PDE forward models with random coefficient fields,” at the Applied Inverse Problems Conference in Grenoble, France.
AEOLUS co-PI Clayton Webster served on the Organizing Committee for the Workshop on Sparse Grid and Applications; Institute for Advanced Study, Technische Universität München, Munich, Germany.
AEOLUS co-PI Francis J. Alexander gave a talk On the Connection between Optimal Uncertainty Quantification and the Mean Objective Cost of Uncertainty, presented at US National Congress on Computational Mechanics (USNCCM), Austin, Texas, July 29, 2019
Marzouk gave an invited plenary lecture at the 12th International Workshop on Monte Carlo Methods and Applications (MCM2019, http://www.mcm2019.unsw.edu.au), Sydney, Australia.
Chen gave an invited talk “Optimal design of acoustic cloak under uncertainty” at the 15th U.S. National Congress on Computational Mechanics, Austin, US
Chen gave an invited talk “Stein variational methods for Bayesian optimal experimental design” at the Applied Inverse Conference in Grenoble, France.
Chen gave an invited talk “Stein variational, reduced basis Bayesian inversion” at the International Congress on Industrial and Applied Mathematics (ICIAM 2019)
Chen gave an invited talk “A scalable method for PDE-constrained optimization under high-dimensional uncertainty” at the International Congress on Industrial and Applied Mathematics (ICIAM 2019)
June 2019
AEOLUS co-PI George Biros gave the Argyris Lecture at the University of Stuttgart titled “Towards direct numerical simulation of blood flow in microcirculation"
AEOLUS co-PI George Biros gave an invited talk titled “Reduced order models for nonlinear boundary value problems with moving interfaces” at the Sandia National Labs (NM).
Ghattas gave the Oden Lecture at the XVIth Conference on the Mathematics of Finite Elements and Applications (MAFELAP 2019), London, UK.
Willcox gives a Keynote Talk "Predictive Data Science for Physical Systems: From Model Reduction to Scientific Machine Learning" at the New York Scientific Data Summit, New York, NY, June 2019.
May 2019
AEOLUS co-PI George Biros gave the Argyris Lecture at the University of Stuttgart titled “Towards direct numerical simulation of blood flow in microcirculation"
AEOLUS co-PI George Biros gave an invited talk titled “Reduced order models for nonlinear boundary value problems with moving interfaces” at the Sandia National Labs (NM).
Ghattas gave the Oden Lecture at the XVIth Conference on the Mathematics of Finite Elements and Applications (MAFELAP 2019), London, UK.
Willcox gives a Keynote Talk "Predictive Data Science for Physical Systems: From Model Reduction to Scientific Machine Learning" at the New York Scientific Data Summit, New York, NY, June 2019.
April 2019
The Oden Institute and Sandia National Laboratories co-host Rising Stars in Computational & Data Sciences, bringing 32 outstanding female PhD students and postdocs to Austin for a two-day intensive research workshop.
AEOLUS graduate student Teresa Portone gives an invited talk “A Stochastic Operator Representation of Model-Form Uncertainty” at Rising Stars in Computational & Data Sciences 2019.
AEOLUS Co-PI Clayton Webster presents a Keynote lecture on Learning high-dimensional systems from incomplete data by optimal non-linear approximations, Isaac Newton Institute for Mathematical Sciences, University of Cambridge, Cambridge, United Kingdom.
Marzouk gives invited talks at INRIA, Laboratoire Jean Kuntzmann. Grenoble, France; Schlumberger-Doll Research. Cambridge, MA; Auburn University, Department of Mathematics and Statistics, Colloquium. Auburn, AL; Worcester Polytechnic Institute, Department of Mathematical Sciences, Colloquium. Worcester, MA.
Willcox give the Keynote Talk "Data to Decisions: Computational Methods for the Next Generation of Engineering Systems" at the SIAM Central Valley Regional Student Conference, University of California, Merced, April 2019
Willcox gives the Charlemagne Distinguished Lecture "Projection-based model reduction: Formulations for Physics-based Machine Learning" at RWTH Aachen, April 2019.
Moser gives an invited lecture entitled "Making Reliable Computational Predictions: Is it Possible" at Computational $ Data Enabled Science Days at SUNY Buffalo.
March 2019
Ghattas received the 2019 SIAM Geosciences Career Prize, for "groundbreaking contributions in analysis, methods, algorithms, and software for grand challenge computational problems in geosciences, and for exceptional influence as mentor, educator, and collaborator."
AEOLUS graduate student Teresa Portone gives an invited talk “A Stochastic Operator Approach to Representing Model-Form Uncertainty” at Sandia National Laboratories, Albuquerque, NM.
Chen gave an invited seminar talk "Hessian in action for high-dimensional model reduction, stochastic optimization, and Bayesian inversion" at Department of Mathematics, Peking University, China
Chen lectured a short course “Approximation of high-dimensional parametric PDEs” at Department of Mathematics, Peking University, China
February 2019
Ghattas gave an invited talk entitled “Large-scale Optimal Experimental Design for Bayesian Nonlinear Inverse Problems,” at the SIAM Conference on Computational Science and Engineering, (CSE19) in Spokane, WA
Ghattas and former Oden Institute and DiaMonD (MMICC-1) members Tobin Isaac, Noemi Petra, and Georg Stadler received the 2019 SIAM SIAG on Computational Science & Engineering Best Paper Prize (for the period 2015–2018) for the paper "Scalable and Efficient Algorithms for the Propagation of Uncertainty from Data through Inference to Prediction for Large-scale Problems, with Application to Flow of the Antarctic Ice Sheet," published in 2015 in the Journal of Computational Physics. Watch Toby present the prize lecture at CSE19.
Willcox gives a Keynote Talk "Projection-based model reduction: Formulations for Physics-based Machine Learning" at the LANL Workshop on Machine Learning for Computational Fluid and Solid Dynamics, February 2019.
Chen gave an invited talk “Towards Breaking the Curse of Dimensionality for PDE-constrained Optimization under High-dimensional Uncertainty” at SIAM Conference on Computational Science and Engineering
AEOLUS graduate student Joshua Chen gave a talk "Dimension Adaptive Sparse Quadrature and Sparse Polynomial Parametrized Transport Maps for High Dimensional Bayesian Integration" at SIAM Conference on Computational Science and Engineering
AEOLUS graduate student Keyi Wu gave a talk "A Stein variational Newton method for Optimal Experimental Design" at SIAM Conference on Computational Science and Engineering
AEOLUS postdoc Ilona Ambartsumyan presented a poster "An Edge-preserving Method for Joint Infinite–dimensional Bayesian Inversion" at SIAM Conference on Computational Science and Engineering
AEOLUS graduate student Teresa Portone gave a talk "An Uncertainty Representation for Model Inadequacy in a Field-scale Contaminant Transport Model" at SIAM Conference on Computational Science and Engineering.
January 2019
Ghattas began a two-year term as Chair of the SIAM Activity Group on Uncertainty Quantification (SIAG/UQ)
The AEOLUS team presented four posters at the Department of Energy ASCR PI Meeting.

Posters:
| Transport-Based Variational Bayesian Methods for Learning from Data
| Block Copolymer Directed Self-Assembly: Optimal Design of Nanoscale Manufacturing Under Uncertainty
| Learning low-dimensional models via operator lifting and natural greedy algorithms
| Optimal Control under Uncertainty and Multiscale Heterogeneous Materials Modeling in Additive Manufacturing
AEOLUS Co-PI Clayton Webster presents the Tianyuan Distinguished lecture on Learning high-dimensional systems from incomplete data by nonlinear approximation and deep networks; School of Mathematics, Jilin University, Changchun, China.
Ghattas gave a plenary talk entitled "Physics-Based Learning of Complex Models from Large-Scale Data: A Scalable Bayesian Inversion Approach," at the International Conference on Big Data in the Geosciences, China University of Geosciences, Wuhan, China.
Marzouk and Webster are invited speakers at the Johns Hopkins University, USACM workshop on Uncertainty Quantification in Computational Solid and Structural Materials Modeling, Baltimore, MD.
Ghattas and Marzouk are on the editorial board of the new journal, Foundations of Data Science, published by the American Institute of Mathematical Sciences.
Marzouk began a two-year term as program director of the SIAM Activity Group on Mathematical Issues in the Geosciences (SIAG/GS).
Webster is elected President, SIAM Southeastern Atlantic Section; 2019 - 2021
December 2018
AEOLUS PI Willcox visits LLNL and SNL Livermore to discuss research collaborations, and gives a talk "Lift & Learn: From nonlinear PDEs to low-dimensional polynomial approximations."
AEOLUS Co-PI Clayton Webster presents a Distinguished lecture at the Pacific Institute for the Mathematical Sciences (PIMS) , IRMACS Theatre, Simon Fraser University, Burnaby, BC.
Marzouk gave an invited talk at the University of Michigan Institute for Computational Discovery and Engineering, Ann Arbor, MI.
November 2018
AEOLUS co-PI Clayton Webster served as the Co-Chair of rSurrogate models for UQ in complex systems; Isaac Newton Institute for Mathematical Sciences, University of Cambridge, Cambridge, United Kingdom. Workshop Website
The AEOLUS team met in person for a project kick-off meeting in Austin, TX.
October 2018
Karen Willcox is part of the Planning Committee on the Workshop on the Frontiers of Mechanistic Data-Driven Modeling for Additive Manufacturing, The National Academies.
Ghattas gave an invited talk entitled “Learning from data through the lens of models: Scalable algorithms for Bayesian inverse problems,” at the Workshop on HPC and Data Science for Scientific Discovery, at the Institute for Pure and Applied Mathematics (IPAM), UCLA, Los Angeles, CA
Ghattas gave the Charlemagne Distinguished Lecture at RWTH Aachen University, Germany. The lecture was entitled "Large-scale Bayesian inversion with applications to flow of the Antarctic ice sheet."
Marzouk gave a colloquium talk at Duke University, Department of Civil and Environmental Engineering.
Marzouk gave an invited talk at the Finnish Meteorological Institute, Helsinki, Finland.
Chen gave an invited talk “Sparse quadrature for high-dimensional Bayesian inverse problems” at the 4th annual meeting of SIAM central states section, Oklahoma.
AEOLUS postdoc Ilona Ambartsumyan gave a talk “Bayesian inversion of fault properties in two-phase flow in fractured media” at the Annual Meeting of the SIAM Texas-Louisiana Section, LSU, Baton Rouge, Louisiana
September 2018
Ghattas gave an invited talk entitled “Scalable algorithms for optimal training data for Bayesian inference of large scale models,” at the Workshop on Big Data Meets Large-Scale Computing, Institute for Pure and Applied Mathematics (IPAM), UCLA, Los Angeles, CA
Willcox gave invited tutorials on "Multifidelity Models and Methods: Fusing models and data to achieve efficient design, optimization, and uncertainty quantification" and "Model Order Reduction: Approximate yet accurate surrogates for large-scale simulation" as part of the thematic program on Science at Extreme Scales: Where Big Data Meeting Large-Scale Computing, Institute for Pure and Applied Mathematics, September 2018