### 2019

(2019/12) Xun Huan gave a presentation “Simulation-based 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 the

*Journal of Geophysical Research: Oceans*.(2019/11) Xun Huan gave a presentation “Finding the Most Useful Data via Simulation-based 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 PhD Qualifying Exams!

(2019/09) Our paper “Design optimization of a scramjet under uncertainty using probabilistic learning on manifolds” is published in the

*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. [Slides]

(2019/08) Xun Huan gave a tutorial lecture “Introduction to Optimal Experimental Design” at the Uncertainty Quantification Summer School. [Slides]

(2019/07) U.S. National Congress on Computational Mechanics (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 Pattern-forming 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 pattern-formation: Inference under varying fidelity and noise” is published in the

*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 Physics-Based Models” at TU Kaiserslautern Scientific Computing Seminar.

(2019/06) Our paper “Embedded Model Error Representation for Bayesian Model Calibration” is published in the

*International Journal for Uncertainty Quantification*.(2019/06) Beckett Zhou gave a presentation “Towards Real-Time In-Flight Ice Detection Systems via Computational Aeroacoustics and Bayesian Neural Networks” at the AIAA Aviation Forum [conference 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 “Entropy-based closure for probabilistic learning on manifolds” has been published in the

*Journal of Computational Physics*.(2019/03) Xun Huan gave a presentation “Finding the most useful data via simulation-based Bayesian experimental design” at the University of Michigan Applied and Interdisciplinary Mathematics (AIM) Seminar.

(2019/03) SIAM Conference on Computational Science and Engineering

- Xun Huan gave a presentation “Global Sensitivity Analysis for Random Fields in Large-Eddy 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”.

(2019/03) Xun Huan co-organized a two-part minisymposium “Optimal Experimental Design for Inverse Problems” (parts I, II) at the SIAM Conference on Computational Science and Engineering.

(2019/01) Our paper “Compressive sensing adaptation for polynomial chaos expansions” has been published in the

*Journal of Computational Physics*.(2019/01) AIAA SciTech Forum

- Xun Huan gave a presentation “Uncertainty Propagation Using Conditional Random Fields in Large-Eddy Simulations of Scramjet Computations” [conference paper].
- Gianluca Geraci gave a presentation “Progress in Scramjet Design Optimization Under Uncertainty Using Simulations of the HIFiRE Direct Connect Rig” [conference paper].

### 2018

(2018/12) Our paper “Enhancing Model Predictability for a Scramjet Using Probabilistic Learning on Manifolds” has been published in the

*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 Model-based 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 Co-Optima Gasoline Fuel Blends” has been published in the

*SAE International Journal of Fuels and Lubricants*.(2018/08) Jeremiah Hauth and Wanggang Shen joined the group!

(2018/06) Our paper “Compressive sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions” has been published in the

*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 the

*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 “Simulation-Based 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 “Simulation-based 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 Manchester-Southampton-Glasgow 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) Xun Huan gave a presentation “Compressive Sensing with Cross-Validation and Stop-Sampling for Sparse Polynomial Chaos Expansions” at the SIAM Conference on Uncertainty Quantification.

(2018/04) Xun Huan co-organized a three-part minisymposium “Model-Based Optimal Experimental Design” (parts I, II, III) at the SIAM Conference on Uncertainty Quantification.

(2018/02) Xun Huan gave a presentation “Optimal Sequential Bayesian Experimental Design” at the workshop “Foresight for Making Good Future Predictionsâ€”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 [conference 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.