Johannes Voss is staff scientist at SLAC National Accelerator Laboratory. He leads the data science and electronic structure method efforts at the SUNCAT Center for Interface Science and Catalysis. The team develops machine learning models for the accurate and efficient prediction of catalytic reaction energies and materials properties. These developments include exchange-correlation functionals for computational surface science and efficient beyond density functional theory approaches.
Within the Ultrafast Catalysis FWP at SLAC, he leads the efforts of X-ray spectra simulations for understanding of ultrafast surface chemistry as observed using free-electron lasers.