Edited by Dr.Douglas Allaire, 2016, 2017 Edited by Kaiyu Li, 2016, 2017 Edited by Benson Isaac, 2018, 2019 Edited by Anyone afterwards, write your name here. researchtransparent600#500000 Research OverviewCollaborators Research The research at the lab focuses on the development of computational methods for the analysis, design, and operation of complex systems. We are currently specifically interested in aspects of optimization, uncertainty quantification, and machine learning for simulation-based design. Often, these methods involve the use of multiple sources of information, which we refer to as multifidelity methods, or more generally, multi-information source methods. Current projects involve the development of computational methods for enabling autonomous materials discovery, the development of optimal algorithms for multi-information source management in design of materials and materials systems, and optimal sample-based uncertainty quantification. Current Research current-researchtransparent600#500000 Autonomous Materials DiscoveryULTIMATEMIS-BO for Microstructure PerformancePSP vs PP Enabling Self Aware UAVsAdaptive Multifidelity Experimental DesignActive Subspace Multifidelity Bayesian Optimization Raymundo Arroyave, Professor of Materials Science and Engineering at Texas A&M University Danny Perez, Technical Staff Member, T-1, Los Alamos National Laboratory Ankit Srivastava, Associate Professor of Materials Science and Engineering at Texas A&M University Ibrahim Karaman, Professor and Department Head of Materials Science and Engineering at Texas A&M University John Jakeman, Principal Member of the Technical Staff, Sandia National Laboratories Alex Gorodetsky, Assistant Professor of Aerospace Engineering at University of Michigan Karen Willcox, NAE, Professor, Director, Oden Institute for Computational Engineering and Sciences at University of Texas, Austin