Kevin Carlberg is a Principal Member of Technical Staff at Sandia National Laboratories in Livermore, California. He leads a research group of PhD students, postdocs, and technical staff whose work combines concepts from machine learning, computational physics, and high-performance computing to drastically reduce the cost of simulating nonlinear dynamical systems at extreme scale.
Current national-security applications include a range of problems in mechanical and aerospace engineering such as hypersonic vehicles, turbulent flows over store-in-cavity configurations, and high-speed gas-transfer systems.
His recent plenary talk at the ICERM Workshop on Scientific Machine Learning summarizes his group’s work.
Personal website: https://kevintcarlberg.net