Kevin Carlberg is a Distinguished 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.
PhD in Aeronautics and Astronautics, 2011
MS in Aeronautics and Astronautics, 2006
BS in Mechanical Engineering, 2005
Washington University in St. Louis