Welcome to new postdoc Marco Tezzele who joins us from SISSA. Marco is an expert on reduced-order modeling and design optimization. He will be joining our NASA ULI project and leading the effort to build digital twins in support of scalable autonomous cargo operations.
Welcome to new postdoc Matteo Croci who joins us from Oxford. Matteo is an expert on multilevel Monte Carlo and numerical methods for PDEs. He will be joining the PSAAP project.
Congratulations to Rudy Geelen for having his paper Localized non-intrusive reduced-order modeling in the operator inference framework accepted for publication in Philosophical Transactions of the Royal Society A. The paper presents data-driven learning of localized reduced models. Instead of a global reduced basis, the approach employs multiple local approximation subspaces. This localization permits adaptation of a reduced model to local dynamics, thereby keeping the reduced dimension small. This is particularly important for reduced models of nonlinear systems of partial differential equations, where the solution may be characterized by different physical regimes or exhibit high sensitivity to parameter variations. Localization has been used in a number of model reduction approaches in the past; the key contribution here is the non-intrusive formulation via Operator Inference.
Congratulations to Parisa Khodabakhshi for having her paper Non-intrusive data-driven model reduction for differential algebraic equations derived from lifting transformations accepted for publication in Computer Methods in Applied Mechanics and Engineering. The paper presents a non-intrusive data-driven approach for model reduction of nonlinear systems. The approach considers the particular case of nonlinear PDEs that form systems of partial differential algebraic equations when lifted to polynomial form. Such systems arise, for example, when the governing equations include Arrhenius reaction terms (e.g., in reacting flow models) and thermodynamic terms (e.g., the Helmholtz free energy terms in a phase-field solidification model).
Welcome to new postdoc Aniketh Kalur. Aniketh just completed his PhD at the University of Minnesota on "Reduced-Complexity Modeling for Control and Nonlinear Analysis of Transitional Flows."
Karen will be giving a keynote talk on Predictive Digital Twins at The 13th International Symposium on NDT in Aerospace 2021.
Karen will be giving a plenary talk on Research Needs and Future Directions in Aviation Digital Twins: Applications and Opportunities, hosted by the MITRE Corporation.
Welcome to new Willcox group students Ben Zastrow (Aerospace Engineering) and Valentyn Visyn (Computational Science, Engineering and Mathematics).
Congratulations to former Kiwi group graduate student and HKUST Assistant Professor Rhea Liem for being selected as the 2021 recipient of Hong Kong's University Grants Committee Teaching Award!
Michael, Ionut and Anirban will all be giving a technical talks at the Conference on Mechanistic Machine Learning and Digital Twins for Computational Science, Engineering and Technology.
Karen will be giving a keynote talk on Predictive Digital Twins at the Computing in Engineering Forum, hosted by the University of Wisconsin-Madison.
Omar Ghattas and I have a paper in the 2021 volume of Acta Numerica. Learning physics-based models from data: Perspectives from inverse problems and model reduction gives a 110-page introduction to inverse problems and model reduction, representing some of our 16 years of collaboration. The paper is available open access.
Congratulations to Julie Pham for being named one of Aviation Week Network’s 20 Twenties!
Congratulations to Anirban Chaudhuri and Boris Kramer for having their paper Certifiable Risk-Based Engineering Design Optimization accepted to AIAA Journal. This paper proposes two notions of certifiability: the first is based on accounting for the magnitude of failure to ensure data-informed conservativeness, and the second is the ability to provide optimization convergence guarantees by preserving convexity. Satisfying these notions leads to certifiable risk-based design optimization (CRiBDO).
Michael Kapteyn's digital twin research is highlighted on the Department of Energy Office of Science website.
Our paper Modeling COVID-19 disruptions via network mapping of the Common Core Mathematics Standards is a finalist for Best Paper in the Computers in Education section of the ASEE Annual Conference & Exposition. Congratulations to Luwen Huang and Kayla Bicol!
Karen is giving an Invited Plenary talk at the European Control Conference (ECC21) on Thursday July 1.
Best wishes to postdoc James Koch who is leaving to start a staff research position at Pacific Northwest National Laboratory.
Congratulations to Stefanie Salinger for completing her master's thesis "Toward Predictive Digital Twins for Self-Aware Unmanned Aerial Vehicles: Non-Intrusive Reduced Order Models and Experimental Data Analysis." Stefanie performed an amazing pivot to reduced order modeling when the pandemic shut down her UAV hardware experiments. Stefanie will be starting a position at Lockheed Martin in Fort Worth.
Welcome to new Oden Institute master's student Vignesh Sella.
I was honored to testify to Congress for the Subcommittee on Energy of the House Committee on Science, Space, and Technology hearing on Accelerating Discovery: the Future of Scientific Computing at the Department of Energy. My written testimony is posted here.
Congratulations to PhD student Michael Kapteyn for having his paper A Probabilistic Graphical Model Foundation for Enabling Predictive Digital Twins at Scale published in Nature Computational Science. This paper proposes a probabilistic graphical model as a formal mathematical representation of a digital twin and its associated physical asset. This formulation naturally integrates data, predictive models, and decisions. We illustrate the approach by building a structural digital twin of our group's unmanned aerial vehicle (UAV) hardware asset and show how the digital twin enables dynamic mission re-planning in response to in-flight structural damage.
Our perspective Scaling Digital Twins from the Artisanal to the Industrial was published in Nature Computational Science. This opinion piece makes the case that advancing the mathematical and algorithm foundations is essential to achieving digital twins at scale. It draws from examples in cardiology and aerospace engineering.
Congratulations to Michael Kapteyn for a successful PhD defense!
PhD student Michael Kapteyn's research will be presented next week at a NATO Science and Technology Organization (STO) Applied Vehicle Technology Panel (AVT) Research Workshop on Intelligent Solutions for Improved Mission Readiness of Military UxVs.
Congratulations to postdoc Parisa Khodabakhshi for having her paper A multifidelity method for a nonlocal diffusion model accepted for publication in Applied Mathematics Letters. This paper puts forward the idea that the horizon δ in a nonlocal model can be used to generate a hierarchy of multifidelity models, similar to using the grid size h to create multilevel models. The paper develops this idea in the context of forward uncertainty quantification using a multifidelity Monte Carlo formulation. Another great collaboration with Max Gunzburger!
Together with Patrick Heimbach and Omar Ghattas, Karen co-authored a comment piece The imperative of physics-based modeling and inverse theory in computational science in Nature Computational Science. We make the case that inverse theory has a key role to play in the data-driven future of computational science, especially for applications in the physical/nature world where data are sparse.
Congratulations to MIT Mapping Lab researcher Luwen Huang for having her paper Network models and sensor layers to design adaptive learning using educational mapping accepted in Design Science. This paper defines "Micro-outcomes" as extremely fine-grained statements of learning ability and then shows how network modeling can be used to design a sensor layer of high-resolution assessments. When put together, this forms the mathematical and computational foundation for intelligent tutoring, intelligent teaching assistants, and data-driven teaching feedback. We describe our deployment of the ideas in College Algebra and Introductory Accounting subjects at Arapahoe Community College and Quinsigamond Community College, and in the MIT sophomore Aerospace Engineering class Signals and Systems.
Congratulations to former visiting PhD student Max Ehre for having his paper Conditional reliability analysis in high dimensions based on controlled mixture importance sampling and information reuse accepted for publication in Computer Methods in Applied Mechanics and Engineering. This paper employs information reuse to reduce the computational cost of conditional reliability analysis.
Karen is giving an Invited Plenary talk on "A Probabilistic Graphical Model Foundation for Enabling Predictive Digital Twins at Scale" at the SIAM Conference on Computational Science and Engineering (CSE21) on Tuesday March 2.
Elizabeth, Graham, Ionut, Mengwu, Michael, Parisa, Sean and Shane will all be presenting at SIAM Conference on Computational Science and Engineering (CSE21) March 1-5. The group's favorite conference; sorry to miss it in person!
Congratulations to postdoc Mengwu Guo who this month starts his tenure-track faculty position as Assistant Professor in the Department of Applied Mathematics at University of Twente. Best wishes Mengwu!
Congratulations to former postdoc Qifeng Liao who just received tenure at ShanghaiTech. Best wishes for the next phase of your career Qifeng!
Congratulations to former PhD student Victor Singh for having his paper Decision Making Under Uncertainty for a Digital Thread Enabled Design Process accepted for publication in the Journal of Mechanical Design. This paper presents a formulation of decision under uncertainty with Digital Thread, using Bayesian statistics and decision theory.
Karen is giving a keynote talk on "Aerospace Design in the Age of Big Data and Big Compute" at the AIAA Scitech Forum on Tuesday January 19.
Congratulations to PhD student Shane McQuarrie for having his paper Data-driven reduced-order models via regularized operator inference for a single-injector combustion process accepted for publication in the Journal of the Royal Society of New Zealand. This paper derives predictive reduced-order models for rocket engine combustion dynamics via our Operator Inference approach, a scientific machine learning approach that blends data-driven learning with physics-based modeling. The codes and example problems are available on Github.
Karen is giving an invited talk the Machine Learning for Engineering Modeling, Simulation and Design workshop at NeurIPS 2020.
Congratulations to Elizabeth Qian for a successful PhD defense!
Congratulations to PhD student Michael Kapteyn for winning the 2020 AIAA Best MDO Paper Prize for his paper Toward predictive digital twins via component-based reduced-order models and interpretable machine learning. This award is presented to the paper selected from among all AIAA papers published at MDO sessions in 2020 AIAA conferences.
Congratulations to Anirban for having his paper mfEGRA: Multifidelity Efficient Global Reliability Analysis through Active Learning for Failure Boundary Location accepted to Structural and Multidisciplinary Optimization. The paper develops a multifidelity version of the popular EGRA method, which is used for locating contours (e.g., failure boundaries, stability boundaries). The multifidelity formulation provides significant computational speedups.
Congratulations to postdoc Ionut Farcas for being awarded the Heinz Schwaertzel prize for his PhD thesis. This prize is awarded to the best PhD thesis in fundamentals of computer science that was submitted to any university in Munich in the previous two years.
Karen's keynote talk on Scientific Machine Learning at JuliaCon is posted on youtube here.
Karen had an opinion piece on Scientific Machine Learning published in Aerospace Testing International.
Karen has been elected to the AIAA Board of Trustees.
Welcome to new postdoc James Koch, who joins us from University of Washington. James is an expert in propulsion (particularly rotating detonation engines) and nonlinear dynamical systems. He will be working on combining physics-based modeling and data-driven learning for the challenging problems in our Air Force Center of Excellence on Multi-fidelity Modeling of Rocket Combustion Dynamics.
Congratulations to Michael Kapteyn for having his paper Data-driven physics-based digital twins via a library of component-based reduced-order models accepted for publication in International Journal for Numerical Methods in Engineering. This paper will appear as part of a special issue on Digital Twins. This work is collaborative with David Knezevic, Phuong Huynh and Minh Tran of Akselos.
Congratulations to Elizabeth Qian for being selected as a winner of the 2020 SIAM Student Paper Prize for her paper Multifidelity Monte Carlo estimation of variance and sensitivity indices. The paper appeared in SIAM/ASA Journal on Uncertainty Quantification in 2018. This paper is joint work with our DiaMonD collaborators Monty Vesselinov and Dan O'Malley at Los Alamos National Laboratory.
Welcome to new postdoc Rudy Geelen, who joins us from Duke University. Rudy is an expert in phase-field models for fracture. He will be working as part of the AEOLUS team to develop reduced-order modeling and uncertainty quantification methods in our additive manufacturing and materials testbed application problems.
Welcome to new postdocs Mengwu Guo and Ionut Farcas. Mengwu joined the group in January, from EPFL. His research expertise includes reduced-order modeling, uncertainty quantification, and scientific machine learning. Ionut joined the group in February, from TU Munich. His research expertise includes multifidelity modeling, reduced-order modeling, sparse grids, and high performance computing.
Congratulations to Elizabeth Qian for having her paper Lift & Learn: Physics-informed machine learning for large-scale nonlinear dynamical systems accepted for publication in Physica D: Nonlinear Phenomena. The paper lays the theoretical foundations for a new physics-informed machine learning method for systems governed by nonlinear partial differential equations. The Lift & Learn method uses lifting transformations, which introduce auxiliary variables to expose polynomial structure. This polynomial structure is exploited to achieve non-intrusive learning from simulation snapshot data, through the lens of projection (which preserves polynomial structure). Elizabeth's analysis of the method shows that in some settings Lift & Learn models recover the generalization accuracy of intrusive projection-based reduced models.
Congratulations to Max Opgenoord and Doug Allaire for having their paper Variance-based sensitivity analysis to support simulation-based design under uncertainty recognized as one of the top 10 most accessed articles in Journal of Mechanical Design in 2019.
Congratulations to Renee Swischuk and Boris Kramer for having their paper Learning physics-based reduced-order models for a single-injector combustion process accepted to AIAA Journal. This work is collaborative with Dr. Cheng Huang on our Air Force Center of Excellence on Multi-fidelity Modeling of Rocket Combustion Dynamics and shows the power of our non-intrusive Lift & Learn model reduction method on a challenging combustion example.
Congratulations to Anirban Chaudhuri and Boris Kramer for having their paper Information Reuse for Importance Sampling in Reliability-Based Design Optimization accepted to Reliability Engineering and System Safety.
Congratulations to PhD student Michael Kapteyn for winning the Southwest Research Institute Student Paper Prize for his AIAA Scitech paper Toward predictive digital twins via component-based reduced-order models and interpretable machine learning.
Congratulations to Laurence Cook for his paper Design optimization using multiple dominance relations being accepted to International Journal for Numerical Methods in Engineering.
Congratulations to Remi Lam for his paper Multifidelity dimension reduction via active subspaces being accepted to SIAM Journal on Scientific Computing.
Karen, Anirban and Michael will all be at the 2020 AIAA Scitech meeting in Orlando. MIT PhD student Michael Kapteyn will present Toward predictive digital twins via component-based reduced-order models and interpretable machine learning on Monday January 6. Karen will present Learning physics-based reduced-order models for a single-injector combustion process on Wednesday January 8. MIT postdoc Anirban Chaudhuri will present Multifidelity Cross-Entropy Estimation of Conditional Value-at-Risk for Risk-Averse Design Optimization in the Managing Multiple Sources of Information MURI Special Session on Friday January 10.
Congratulations to Alex Marques, Max Opgenoord, Remi Lam and Anirban Chaudhuri for their paper A multifidelity method for locating aeroelastic flutter boundaries being accepted to AIAA Journal. Great to see the collaboration among different group members bringing different aspects of multifidelity modeling together to develop a method that can produce accurate estimates of the flutter boundary at a reduced cost by combining information from low- and high-fidelity aeroelastic models.
The video of Karen's invited talk on Predictive Data Science at ICIAM 2019 is posted here. The slides are available here.
Karen is giving an invited talk at SC19. Here are her presentation slides on Predictive Data Science, highlighting our work building an unmanned aerial vehicle and its Digital Twin.
Congratulations to former postdoc Laurence Cook for having his paper Optimization under turbulence model uncertainty for aerospace design accepted in Physics of Fluids. This work is collaborative with Jerome Jarrett of Cambridge University and Aashwin Mishra and Gianluca Iaccarino of Stanford University.
Our Operator Inference python implementation is now available here on github. This package lets you learn reduced-order models with polynomial structure from state snapshot data.
Karen is giving a Keynote Talk at the 2019 INFORMS Annual Meeting.
Karen is giving an Invited Talk at the 2019 European Numerical Mathematics and Advanced Applications Conference.
Congratulations to former group member Alex Feldstein for having his paper Multifidelity Data Fusion with Application to Blended-Wing-Body Multidisciplinary Analysis Under Uncertainty accepted for publication in AIAA Journal. This paper shows how multifidelity modeling brings higher fidelity information from both simulation and experimental data into early-stage design processes, enabling better decision-making and earlier identification of key system risks. The paper is co-authored with David Lazzara and Norm Princen from Boeing.
Karen is giving the Kalman Lecture at the University of Potsdam Institute of Mathematics.
Karen has been appointed External Professor at the Santa Fe Institute.
Karen 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.
Check out our new page on nonlinear model reduction. Python scripts for our Lift & Learn non-intrusive model reduction approach will be available soon.
Karen 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.
Congratulations to MIT PhD student Michael Kapteyn for having his paper Distributionally Robust Optimization for Engineering Design under Uncertainty accepted for publication in the International Journal for Numerical Methods in Engineering.
MIT PhD student Elizabeth Qian will present Transform & Learn: A data-driven approach to nonlinear model reduction at AIAA Aviation on Friday June 21.
Karen is giving a keynote talk on Predictive Data Science at the New York Scientific Data Science Summit on Friday June 14.
Karen is giving an invited talk on Interdisciplinary Research and Education for a Computational Future at the Aspen Symposium hosted by Forum for the Future of Higher Education.
Congratulations to the group's most recent PhD graduates on their hooding celebrations. Dr. Harriet Li is heading to JHU Applied Physics Lab, Dr. Victor Singh is heading to Boeing, and Dr. Max Opgenoord is already at Amazon Prime Air.
Congratulations to SM student Renee Swischuk for successfully completing an outstanding SM thesis, "Physics-based machine learning and data-driven reduced-order modeling."
Congratulations to PhD student Harriet Li for successfully defending her PhD thesis, "Scalable Online Nonlinear Goal-Oriented Inference with Physics-Informed Maps."
Congratulations to Boris Kramer and Alex Marques for their paper Multifidelity probability estimation via fusion of estimators being accepted to Journal of Computational Physics, and to Max Opgenoord for his paper Design for Additive Manufacturing: Cellular Structures in Early-Stage Aerospace Design being accepted to Structural and Multidisciplinary Optimization. This brings up 100 group papers being published in archival journals.
Congratulations to PhD student Victor Singh for successfully defending his PhD thesis, "Towards a Feedback Design Process Using Digital Thread."
An amazing two days hosting 37 inspirational young women at the Oden Institute for Rising Stars in Computational and Data Sciences.
Our Department of Energy report on Basic Research Needs for Scientific Machine Learning: Core Technologies for Artificial Intelligence has been released. The short brochure version can be found here.
ICES has a new name! We are now the Oden Institute for Computational Engineering and Sciences, the "Oden Institute'' for short.
Karen is co-organizing the Workshop on Multifidelity Modeling In Support Of Design And Uncertainty Quantification. The workshop will be held Sunday June 16, in conjunction with the AIAA Aviation meeting in Dallas, TX.
Karen was announced as one of the Class of 2019 AIAA Fellows. Thank you to all my students, postdocs and collaborators whose work contributed towards achieving this honor!
Max Opgenoord's paper Influence of Transonic Flutter on the Conceptual Design of Next-Generation Transport Aircraft, has been accepted for publication in AIAA Journal.
The group has two papers at AIAA Scitech. Postdoc Anirban Chaudhuri will present Reusing information for multifidelity active learning in reliability-based design optimization. Postdoc Alexandre Marques will present A multifidelity method for locating aeroelastic flutter boundaries.
An open-source implementation of our CLoVER method for multifidelity adaptive sampling to locate a stability boundary is available here on Github.
Karen is featured in the 2018 Texas Engineer magazine.
ICES is committed to growing the diversity of our field! We are partnering with Sandia National Laboratories to host Rising Stars in Computational and Data Sciences, an intensive workshop for women interested in academic and research careers. The workshop will be held April 9-10, 2019 at ICES. Nominations are due January 22, 2019.
ICES is hiring! Check out our two open tenure-track assistant professor positions, one in Computational Medicine and one at the Interfaces of Computational Science and Data Science.
Postdoc Alexandre Marques is giving a spotlight presentation on CLoVER: Contour location via entropy reduction leveraging multiple information sources at the 2018 NeurIPS Conference. See Alex's poster here.
Congratulations to PhD students Rèmi Lam and Max Opgenoord for starting their new jobs at DeepMind and Amazon, respectively.
Karen is giving a talk on our new lifting method for data-driven nonlinear model reduction at the IPAM program on Science at Extreme Scales: Where Big Data Meets Large-Scale Computing.
Congratulations to former postdoc Benjamin Peherstorfer for starting his new tenure-track position in the Department of Computer Science at the Courant Institute.
Karen is giving a tutorial on multifidelity models and methods at the IPAM program on Science at Extreme Scales: Where Big Data Meets Large-Scale Computing.
Karen is giving a tutorial on model reduction at the IPAM program on Science at Extreme Scales: Where Big Data Meets Large-Scale Computing.
Congratulations to Alexandre Marques and Rèmi Lam on having their paper Contour location via entropy reduction leveraging multiple information sources accepted to the 2018 NeurIPS Conference (21% acceptance rate) and selected for a spotlight presentation (3% acceptance rate).
Check out the ICES September newsletter.
Congratulations to PhD student Max Opgenoord for successfully completing his PhD thesis. Dr. Opgenoord's thesis is an outstanding mix of contributions to both theory and practical design methods. His most significant contributions include a low-order transonic flutter model appropriate for use in early-stage aircraft design (also the winner of an AIAA best paper award) and a computational methodology to achieve aeroelastic tailoring using additive manufacturing. Congratulations Max!
Effective August 1, Karen begins her new position as Director of the Institute for Computational Engineering and Sciences at UT Austin.
Congratulations to SM student Renee Swischuk for having her paper Projection-based model reduction: Formulations for physics-based machine learning accepted for publication in Computers and Fluids. A webpage explaining the implementation and posting the codes and datasets is forthcoming.
Congratulations to postdoc Boris Kramer for having his paper Conditional-Value-at-Risk Estimation via Reduced-Order Models accepted for publication in SIAM/ASA Journal on Uncertainty Quantification. This paper is joint work with our collaborators Matthias Heinkenschloss and Timur Takhtaganov at Rice University.
Karen and PhD student Michael Kapteyn are running water rocket workshops at the New Zealand International Science Festival.
PhD student Michael Kapteyn is profiled with a newspaper article in the New Zealand Herald.
PhD student Max Opgenoord is presenting his paper "Aeroelastic Tailoring using Additively Manufactured Lattice Structures" at the AIAA Aviation Conference in Atlanta, GA.
Congratulations to postdoc Laurence Cook for having his paper Generalized information reuse for optimization under uncertainty with non-sample average estimators accepted for publication in International Journal for Numerical Methods in Engineering.
We are hosting a Workshop on Computational Methods for Design and Control of Next-Generation Engineered Systems at the International Design Centre, SUTD, May 30 to June 1.
Congratulations to PhD student Victor Singh for having his paper Engineering Design with Digital Thread accepted for publication in AIAA Journal.
Congratulations to PhD student Remi Lam for successfully completing his PhD thesis. Dr. Lam's thesis has made excellent contributions in Bayesian optimization for complex systems and in a multi-fidelity formulation for determining an active subspace.
Welcome to new postdoc Dr. Laurence Cook. Laurence previously spent time with the group as a visiting student.
The news is official: Karen will begin a new position as Director of ICES at UT Austin. She starts August 1, 2018. Note that she is no longer taking on new students or postdocs at MIT.
Karen was named a Fellow of SIAM in the 2018 SIAM Fellows list.
Congratulations to PhD student Elizabeth Qian for having her paper Multifidelity Monte Carlo estimation of variance and sensitivity indices accepted for publication in SIAM/ASA Journal on Uncertainty Quantification. This paper is joint work with our DiaMonD collaborators at Los Alamos National Laboratory.
Congratulations to postdoc Boris Kramer and former postdoc Benjamin Peherstorfer for having their paper Multifidelity preconditioning of the cross-entropy method for rare event simulation and failure probability estimation accepted for publication in SIAM/ASA Journal on Uncertainty Quantification.
The group has 7 papers at the upcoming AIAA 2018 Scitech meeting, Jan. 8-12. Alex Feldstein will present on multi-fidelity analysis for Blended Wing Body stability and control (Tues 9.30am); Victor Singh will present on design with digital thread (Tues 11.30am); Michael Kapteyn will present on distributionally robust optimization (Tues 11.30am); Max Opgenoord will present on a low-order flutter model for conceptual design (Tues 2.30pm); and Anirban Chaudhuri, Benjamin Peherstorfer and Karen Willcox will present in the MURI special session on Managing multiple information sources of multi-physics systems (Thurs 0930-1230).
Congratulations to former postdoc Ralf Zimmermann for having his paper Geometric Subspace Updates with Applications to Online Adaptive Nonlinear Model Reduction accepted for publication in SIAM Journal on Matrix Analysis and Applications.
Congratulations to Max Opgenoord for having his paper Towards a Low-Order Model for Transonic Flutter Prediction selected as the AIAA Theoretical Fluid Mechanics Conference Best Paper from the 2017 AIAA Aviation Forum.
Karen is co-organizing an IMA workshop Integrating Machine Learning and Simulation: From Uncertainty Quantification to Digital Twins, to be held March 6-8, 2018.
Our study on gender diversity at MIT, with Luwen Huang and Elizabeth Qian, has been featured on MIT News. Check out the study and the interactive visualization of gender diversity on a class-by-class basis for the past 20 years at kiwi.mit.edu/mit-gender-diversity.
Congratulations to collaborator (and long-time mentor to Karen) Andy Philpott for being named an INFORMS Fellow in the Class of 2017.
Victor Singh is presenting his work on Digital Thread for Engineering Design at the International Workshop on Structural Health Monitoring, held at Stanford September 12-14.
Our review paper on multifidelity methods has been published in SIAM Review — Survey of multifidelity methods in uncertainty propagation, inference, and optimization.
Congratulations to Rèmi Lam on having his paper "Lookahead Bayesian Optimization with Inequality Constraints" accepted to the 2017 NIPS Conference (21% acceptance rate).
Karen and Luwen's paper Network models for mapping educational data has been accepted for publication in Design Science. Interested in implementing a model yourself? Check out the paper's companion webpage for guidelines and sample code.
Our paper is cited as an example of physics-based machine learning in a recent article in SIAM News.
Karen has been appointed as a member of the Department of Energy ASCR study group on mathematics needs for machine learning.
Karen has been appointed as a member of the National Academies Committee to Assess the Risks of Unmanned Aircraft Systems (UAS) Integration.
Our book Model Reduction and Approximation: Theory and Algorithms has been published by SIAM.
Luwen Huang is presenting the paper Mapping the CDIO Curriculum with Network Models, at the 13th International CDIO Conference at the University of Calgary. Check out the paper's companion webpage and slides.
Karen was awarded Member of the New Zealand Order of Merit in the Queen’s Birthday honours.
Karen, Max and Laura are all attending the AIAA Aviation Conference in Denver, CO.
Karen is giving the Stewartson Memorial Lecture plenary talk at the British Applied Mathematics Colloquium 2017 conference at the University of Surrey.
Karen is giving a semi-plenary lecture at the FEF2017 conference in Rome, Italy.
Boris Kramer and Benjamin Peherstorfer's paper Feedback Control for Systems with Uncertain Parameters Using Online-Adaptive Reduced Models has been accepted for publication in SIAM Journal on Applied Dynamical Systems.
Elizabeth Qian's paper A certified trust region reduced basis approach to PDE-constrained optimization has been accepted for publication in SIAM Journal on Scientific Computing.
Karen's presentation slides on Multi-fidelity Monte Carlo Methods for Uncertainty Quantification given at the SIAM Conference on Computational Engineering.
A large number of the group will be attending and presenting at the SIAM Conference on Computational Engineering.
Congratulations to Alex Feldstein on being selected as a winner of Aviation Week and AIAA's "Tomorrow's Engineering Leaders: The 20 Twenties".
Victor Singh's paper Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation, has been accepted for publication in AIAA Journal.
Congratulations to visiting student Laurence Cook for winning the AIAA Southwest Research Institute Student Paper Award in Non-Deterministic Approaches at the AIAA Scitech conference, with his paper Horsetail Matching for Optimization Under Probabilistic, Interval and Mixed Uncertainties.
Our forward-looking report on Research and Education in Computational Science and Engineering is finally finished.
Laura Mainini's paper Data to decisions: Real-time structural assessment from sparse measurements affected by uncertainty has been accepted for publication in Computers and Structures.
Rèmi Lam will present his paper Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach at the 2016 NIPS Conference in Barcelona.
Congratulations to Laura Mainini on starting her new position at United Technologies Research Center, in Cork, Ireland.
Sergio Amaral's paper "A Decomposition-Based Uncertainty Quantification Approach for Environmental Impacts of Aviation Technology and Operation" has been accepted for publication in a special issue on UQ in Design in Artificial Intelligence for Engineering Design, Analysis and Manufacturing.
Our Fly-by-Wire project was covered in the MIT News. Collaborating with community colleges to innovate educational technology
Congratulations to Rèmi Lam for having his paper "Bayesian Optimization with a Finite Budget: An Approximate Dynamic Programming Approach" accepted for the 2016 NIPS Conference.
Congratulations to Benjamin Peherstorfer on accepting a tenure-track faculty position at University of Wisconsin, Madison in the Department of Mechanical Engineering.
Congratulations to Tiangang Cui on accepting a tenure-track faculty position at Monash University in the Department of Mathematics.
Benjamin Peherstorfer's paper Optimal model management for multifidelity Monte Carlo estimation on multi-fidelity uncertainty quantification has been accepted for publication in SIAM Journal on Scientific Computing.
Read our new survey paper on multifidelity methods: Peherstorfer, B., Willcox, K. and Gunzburger, M., Survey of multifidelity methods in uncertainty propagation, inference, and optimization, Technical Report, Aerospace Computational Design Laboratory TR-16-1, 2016.
Max Opgenoord's paper Variance-Based Sensitivity Analysis to Support Simulation-based Design under Uncertainty on distributional sensitivity analysis has been accepted for publication in Journal of Mechanical Design.
Ralf Zimmermann's paper An Accelerated Greedy Missing Point Estimation Procedure on nonlinear model reduction has been accepted for publication in SIAM Journal on Scientific Computing.
Boris Kramer's paper Tangential Interpolation-based Eigenystem Realization Algorithm for MIMO Systems has been accepted for publication in Mathematical and Computer Modelling of Dynamical Systems.
Congratulations to Sergio Amaral (PhD '16) and Max Opgenoord (SM '16) who will receive their degrees at Commencement.
We released the open-source Xoces.js library for mapping learning outcomes.
Benjamin and TC's paper Multifidelity importance sampling has appeared in Computer Methods in Applied Mechanics and Engineering, Vol. 300, pp. 490-509.
Benjamin Peherstorfer's paper Data-driven operator inference for nonintrusive projection-based model reduction has been accepted for publication in Computer Methods in Applied Mechanics and Engineering.
Benjamin Peherstorfer's paper Dynamic data-driven model reduction: Adapting reduced models from incomplete data has been accepted for publication in Advanced Modeling and Simulation in Engineering Sciences.
Sergio Amaral's paper Optimal L2-norm Empirical Importance Weights for the Change of Probability Measure has been accepted for publication in Statistics and Computing.
Max Opgenoord's paper Sensitivity Analysis Methods for Uncertainty Budgeting in System Design has been accepted for publication in AIAA Journal.
Congratulations to Max Opgenoord for completing his SM degree, with his thesis "Uncertainty Budgeting Methods for Conceptual Aircraft Design."
Congratulations to Victor Singh and Max Opgenoord for passing the AeroAstro qualifying exams!
December 9, 2015
Our review paper on parametric model reduction has been published in SIAM Review — A Survey of Projection-Based Model Reduction Methods for Parametric Dynamical Systems
December 1, 2015
Professor Karen E. Willcox is a University of Auckland 2016 Distinguished Alumni Award winner. Press release.
September 30, 2015
We received a 2015 Department of Education's First in the World grant award for our Fly-by-Wire proposal. DoEd press release, Twitter and Facebook post.
July 11-15, 2016
Boris Kramer, Remi Lam and Victor Singh will present their research at the SIAM Annual Meeting in Boston.
July 8, 2016
Boris Kramer will present his paper "Model Reduction for Control of a Multiphysics System: Coupled Burgers' Equation" at ACC 2016.
June 13-17, 2016
Karen will chair a special session on Dynamic Data Driven Applications Systems at the AIAA Aviation Conference in Washington DC. Victor Singh will present on "Methodology for Path Planning with Dynamic Data-Driven Flight Capability Estimation."
June 4, 2016
Karen is on the education panel at the 2016 Alumni Tech Day.
April 19-20, 2016
We are organizing the Workshop on Data to Decisions in Aerospace Engineering at the University of Auckland.
April 4-7, 2016
Benjamin, Boris, Remi and Sergio will attend the SIAM UQ conference in Lausanne, Switzerland.
April 5, 2016
Boris Kramer will present "Control for Systems with Uncertain Parameters" in MS13 at the SIAM UQ conference in Lausanne, Switzerland.
April 1, 2016
Karen will be briefing the results of an online education policy study at the National Academies. Briefing announcement. Release of the final report was covered in the MIT News.
March 30, 2016
Boris Kramer will give a talk "System Identification and Model Reduction for MIMO Systems via the Eigensystem Realization Algorithm" at the the Data-driven Model Order Reduction and Machine Learning conference in Stuttgart, Germany.
March 30 - April 1, 2016
Benjamin is co-organizing the MORML Workshop on Data-driven Model Order Reduction and Machine Learning (MORML 2016).
March 20-25, 2016
Karen, Benjamin, Remi and Elizabeth will be attending the Copper Mountain Conference on Iterative Methods.
January 26, 2016
Karen is giving an invited talk in the Harvard Initiative for Learning and Teaching (HILT) Scholar to Practitioner Speaker Series. Talk announcement.
January 4–8, 2016
Max Opgenoord and Anirban Chaudhuri will be presenting at the AIAA Scitech meeting, San Diego.