AEOLUS: Advances in Experimental Design, Optimization and Learning for Uncertain Complex Systems is a U.S. Department of Energy Mathematical Multifaceted Integrated Capabilities Center (MMICC) involving researchers from Brookhaven National Laboratory, Massachusetts Institute of Technology, Oak Ridge National Laboratory, Texas A&M University, and University of Texas at Austin.


The AEOLUS Center dedicated to developing a unified optimization-under-uncertainty framework for (1) learning predictive models from data and (2) optimizing experiments, processes, and designs, all in the context of complex, uncertain energy systems. The AEOLUS center will address the critical need for a principled, rigorous, scalable, and structure-exploiting capability for exploring parameter and decision spaces of complex forward simulation models.


The AEOLUS team conducts research within eight research sub-thrusts, organized into two integrative research thrusts, and driven by DOE scientific applications.

Driving Scientific Application Area: Advanced Manufacturing & Materials

Additive Manufacturing Testbed

Materials Self-assembly Testbed
(Alexander & Oden)


predictive models via Bayesian inference & optimization
(Webster & Willcox)

experiments, processes, & designs under uncertainty
(Alexander & Ghattas)

Research Sub-Thrusts

Bayesian inference

& Reduced Modeling

Bayesian OED

Optimal Control Under

Scientific Machine Learning

Multiscale Models
& Inadequacy

Optimal Operator

Multifidelity Methods
for OUU

Events & Updates

October 2023
AEOLUS co-PI Biros gives two invited talks at the European Numerical Mathematics and Advanced Applications Conference

September 2023
AEOLUS co-PI Tinsley Oden gave an invited Keynote lecture to Annual Meeting and Summer School 2023 ; IRTG 2379 in Austin on "Phase-Field Models of Phase Change of Complex Systems : Block Copolymers and Growth of VascularTumors", July 2023.

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, 2023, 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 热门软件推荐 - Chrome插件(谷歌浏览器插件):2021-6-13 · 流星加速器 05-09 Everything - 文件搜索工具 05-19 我图网免费下载器 - ppt模板免费下载工具 05-07 EV录屏 - 高清无水印录制软件 05-07 Chrome插件推荐 Google谷歌浏览器最新版Chrome v80 ...

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