2021
 (2021/06) ISBA World Meeting

 Xun Huan gave a presentation “Optimal Bayesian Sequential Design Using Reinforcement Learning with Policy Gradient Methods”.
 Chengyang Huang gave a presentation “Fast Approximate Bayesian Inference via Conditional Generative Adversarial Networks”.
 (2021/05) Our paper “Conceptual Design of Extreme SeaLevel Early Warning Systems Based on Uncertainty Quantification and Engineering Optimization Methods” is published in Frontiers in Marine Science.
 (2021/05) EMI/PMR Conference
 Xun Huan gave a presentation “Optimal Sequential Bayesian Design of Experiments Using Reinforcement Learning with Policy Gradient”.
 Wanggang Shen gave a presentation “Optimal Bayesian Experimental Design for Variational System Identification of Materials Physics Phenomena”.
 (2021/04) Xun Huan gave a presentation “Modelbased sequential experimental design” at the USACM TTA Uncertainty Quantification and Probabilistic Modeling Webinar.
 (2021/03) SIAM CSE
 Aniket Jivani gave a presentation “Multifidelity KarhunenLoeve Expansions for Uncertainty Propagation of Random Field Quantities”.
 Maria Veiga gave a presentation “Including Physical Knowledge into Data Driven Models: Applications in Computational Astrophysics”.
 Saibal De presented a poster “TensorTrain Decomposition for Data Compression and DataDriven Reduced Order Modeling”.
 Jeremiah Hauth gave a presentation “Variational Bayesian Inference for Convolutional Neural Networks in Precision Health Balance Training”.
 Xun Huan gave a presentation “Optimal Experimental Design for Variational System Identification of Material Physics Phenomena”.
 Wanggang Shen gave a presentation “Optimal Bayesian Design of Sequential Experiments using Reinforcement Learning with Policy Gradient Methods”.
 Xun Huan coorganized a minisymposium “ModelBased Optimal Experimental Design” (part 1, 2).
 (2021/02) Our paper “Variational system identification of the partial differential equations governing microstructure evolution in materials: Inference over sparse and spatially unrelated data” is published in Computer Methods in Applied Mechanics and Engineering.
 (2021/01) Congratulations to Snehal Prabhudesai for successfully passing the Ph.D. Qualifying Exam!
 (2021/01) Aniket Jivani gave a presentation “Uncertainty Quantification for a Turbulent Round Jet Using Multifidelity KarhunenLoeve Expansions” at the AIAA SciTech Forum [paper].
 (2021/01) WCCMECCOMAS Congress
 Wanggang Shen gave a presetation “Sequential Optimal Experimental Design Using Reinforcement Learning with Policy Gradient”.
 Xun Huan coorganized a minisymposium “Optimal Experimental Design in Computational Science and Engineering”.
2020
 (2020/12) Xun Huan gave a presentation “Optimal Sequential Bayesian Design of Experiments Using Reinforcement Learning with Policy Gradient” at the Machine Learning in Science & Engineering (MLSE) Conference. [video]
 (2020/12) AGU Fall Meeting
 Yulin Pan presented a poster “Optimal Experimental Design of Sensor Locations in EnKF Data Assimilation for Predicting Oceanic Rogue Waves”.
 Gabor Toth gave a presentation “NextGen Space Weather Modeling Framework Using Physics, Data Assimilation, Uncertainty Quantification and GPUs”.
 (2020/03) COVID19 shutdown.
 (2020/02) Our paper “Uncertainty Propagation Using Polynomial Chaos Expansions for Extreme Sealevel Hazard Assessment: The Case of the Eastern Adriatic Meteotsunamis” is published in Journal of Physical Oceanography.
 (2020/02) Xun Huan gave a presentation “Simulationbased Bayesian Sequential Design Using Reinforcement Learning” at the Michigan State University Department of Statistics and Probability Colloquium.
 (2020/01) AIAA SciTech Forum
 Wanggang Shen gave a presentation “Towards Design of Airfoil Pressure Tap Locations for RealTime Predictions Under Uncertainty Using Bayesian Neural Networks” [paper].
 Jeremiah Hauth gave a presentation “Correlation Effects in Bayesian Neural Networks for Computational Aeroacoustics Ice Detection” [paper].
 Beckett Zhou gave a presentation “Correlation Effects in Bayesian Neural Networks for Computational Aeroacoustics Ice Detection” [paper].
2019
 (2019/12) Xun Huan gave a presentation “Simulationbased optimal sequential Bayesian design using policy gradient reinforcement learning” at the International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics).
 (2019/11) Our paper “Stochastic surrogate model for meteotsunami early warning system in the easter Adriatic Sea” is published in Journal of Geophysical Research: Oceans.
 (2019/11) Xun Huan gave a presentation “Finding the Most Useful Data via Simulationbased Bayesian Experimental Design” at the University of Michigan Integrative Systems + Design (ISD) Manufacturing Seminar Series.
 (2019/11) Congratulations to Jeremiah Hauth and Wanggang Shen for successfully passing the Ph.D. Qualifying Exams!
 (2019/09) Our paper “Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds” is published in Journal of Computational Physics.
 (2019/09) Xun Huan gave a presentation “Optimal Bayesian Design of Sequential Experiments Using Policy Gradient Reinforcement Learning” at the University of Notre Dame Center for Informatics and Computational Science (CICS) Seminar.
 (2019/08) Xun Huan gave a presentation “Uncertainty Quantification via Optimal Experimental Design and Bayesian Neural Networks for Aerospace Applications” at the National Institute of Aerospace Computational Fluid Dynamics Seminar.
 (2019/08) Xun Huan gave a tutorial lecture “Introduction to Optimal Experimental Design” at the Uncertainty Quantification Summer School. [slides]
 (2019/07) USNCCM
 Xun Huan gave a presentation “Linear Experimental Design for Optimal Control Variate Based Surrogate Models”.
 Krishna Garikipati gave a presentation “Variational System Identification of the Partial Differential Equations Governing Patternforming Physics: Inference under Varying Fidelity and Noise”.
 Habib Najm gave a presentation “Uncertainty Quantification in Computational Models of Large Scale Physical Systems”.
 (2019/07) Xun Huan gave a presentation “Sequential Optimal Experimental Design via Reinforcement Learning” at the Workshop on Machine Learning and Uncertainty Quantification.
 (2019/07) Our paper “Variational system identification of the partial differential equations governing the physics of patternformation: Inference under varying fidelity and noise” is published in Computer Methods in Applied Mechanics and Engineering.
 (2019/07) Xun Huan gave a presentation “Policy Gradient Acceleration for Sequential Bayesian Experimental Design” at the Applied Inverse Problems Conference.
 (2019/07) Xun Huan gave a presentation “Optimal Experimental Design and Bayesian Neural Networks for PhysicsBased Models” at TU Kaiserslautern Scientific Computing Seminar.
 (2019/06) Our paper “Embedded Model Error Representation for Bayesian Model Calibration” is published in International Journal for Uncertainty Quantification.
 (2019/06) Beckett Zhou gave a presentation “Towards RealTime InFlight Ice Detection Systems via Computational Aeroacoustics and Bayesian Neural Networks” at the AIAA Aviation Forum [paper].
 (2019/05) Wanggang Shen gave a presentation “Optimal Bayesian design of sequential experiments via reinforcement learning” at the International Conference on Design of Experiments (ICODOE).
 (2019/04) Our paper “Entropybased closure for probabilistic learning on manifolds” has been published in Journal of Computational Physics.
 (2019/03) Xun Huan gave a presentation “Finding the most useful data via simulationbased Bayesian experimental design” at the University of Michigan Applied and Interdisciplinary Mathematics (AIM) Seminar.
 (2019/03) SIAM CSE
 Xun Huan gave a presentation “Global Sensitivity Analysis for Random Fields in LargeEddy Simulations of Scramjet Computations”.
 Khachik Sargsyan gave a presentation “Bayesian Inference for Structural Error Quantification”.
 Andrew Davis gave a presentation “Selecting Multiple Borehole Locations for Maximizing Bayesian Information Gain on Groundwater Transmissivity”.
 Xun Huan coorganized a twopart minisymposium “Optimal Experimental Design for Inverse Problems” (parts I, II).
 (2019/01) Our paper “Compressive sensing adaptation for polynomial chaos expansions” has been published in Journal of Computational Physics.
 (2019/01) AIAA SciTech Forum
 Xun Huan gave a presentation “Uncertainty Propagation Using Conditional Random Fields in LargeEddy Simulations of Scramjet Computations” [paper].
 Gianluca Geraci gave a presentation “Progress in Scramjet Design Optimization Under Uncertainty Using Simulations of the HIFiRE Direct Connect Rig” [paper].
2018
 (2018/12) Our paper “Enhancing Model Predictability for a Scramjet Using Probabilistic Learning on Manifolds” has been published in AIAA Journal.
 (2018/12) Andrew Davis gave a presentation “Selecting Multiple Borehole Locations for Maximizing Bayesian Information Gain on Past Ice Sheet Surface Temperatures” at the AGU Fall Meeting.
 (2018/11) Xun Huan gave a presentation “Finding the Most Informative Data Using Modelbased Bayesian Experimental Design” at the Oakland University Department of Physics Colloquium.
 (2018/10) Our paper “Uncertainty Assessment of Octane Index Framework for Stoichiometric Knock Limits of CoOptima Gasoline Fuel Blends” has been published in SAE International Journal of Fuels and Lubricants.
 (2018/08) Jeremiah Hauth and Wanggang Shen joined the group!
 (2018/06) Our paper “Compressive sensing with CrossValidation and StopSampling for Sparse Polynomial Chaos Expansions” has been published in SIAM/ASA Journal on Uncertainty Quantification.
 (2018/03) Our paper “Global Sensitivity Analysis and Estimation of Model Error, Toward Uncertainty Quantification in Scamjet Computations” has been published in AIAA Journal.
 (2018/08) Xun Huan moved to Ann Arbor, MI to start a new position as an Assistant Professor of Mechanical Engineering at the University of Michigan.
 (2018/07) Joint Statistical Meetings
 Xun Huan gave a speed presentation “SimulationBased Bayesian Optimal Design for Ice Sheet Borehole Experiments” (oral and poster parts).
 Khachik Sargsyan gave a presentation “Bayesian Framework for Embedded Model Error Representation and Quantification”.
 (2018/07) SIAM Annual Meeting
 Xun Huan gave a presentation “Optimal Bayesian Experimental Design of Borehole Locations for Inferring Past Ice Sheet Surface Temperature”.
 Cosmin Safta gave a presentation “Adaptive Sparse Quadrature for Multifidelity Scramjet Flow Simulations”.
 Khachik Sargsyan gave a presentation “Bayesian Inference for Model Error Quantification and Propagation with UQTk”.
 (2018/06) Xun Huan presented a poster “Choosing Embedding for Capturing Model Misspecification Using Global Sensitivity Analysis and Bayes Factor Computation” at the ISBA World Meeting.
 (2018/06) Xun Huan gave a presentation “Simulationbased Bayesian Experimental Design for Computationally Intensive Models” at the University of Cambridge Isaac Newton Institute for Mathematical Sciences, Programme on Uncertainty Quantification for Complex Systems: Theory and Methodologies, and as a part of the ManchesterSouthamptonGlasgow Design of Experiments Seminar Series.
 (2018/06) Xun Huan gave a presentation “Value of Feedback and Lookahead in Bayesian Sequential Optimal Experimental Design” at the Joint Research Conference on Statistics in Quality, Industry, and Technology.
 (2018/04) SIAM UQ
 Xun Huan gave a presentation “Compressive Sensing with CrossValidation and StopSampling for Sparse Polynomial Chaos Expansions”.
 Xun Huan coorganized a threepart minisymposium “ModelBased Optimal Experimental Design” (parts I, II, III).
 (2018/02) Xun Huan gave a presentation “Optimal Sequential Bayesian Experimental Design” at the workshop “Foresight for Making Good Future Predictions—Lookahead Optimization in Artificial and Natural Systems” held by the Santa Fe Institute.
 (2018/01) Xun Huan gave a presentation “Multifidelity Statistical Analysis of Large Eddy Simulations in Scramjet Computations” at the AIAA SciTech Forum [paper].
2017
 (2017/12) Andrew Davis gave a presentation “Optimal Experimental Design of Borehole Locations for Bayesian Inference of Past Ice Sheet Surface Temperatures” at the AGU Fall Meeting.