Research Scientist 4
CurrentInvented and implemented new numerical methods for the solution of Maxwell's equations and the fundamental problem of metrology, the inverse scattering problem.- Invented, implemented, and continuing to develop "Rigorous" method currently being used by customers for the solution of Maxwell's equations for hard x-ray transmission using KLA's Axion machine.- Invented and implemented method for tomography with Axion machine- Invented and implemented competitive Algebraic Neural Network method (simple linear fit for forward problem)- Invented and implemented methods for efficiently calculating the effect of roughness / aperiodicity in the scattering of light from our nominally periodic semiconductor structures, using Axion machine and other machines under development- Influenced the adoption of Bayesian methods / Maximum A Posteriori estimation in several projects within our division of KLA Corp.- Primary skills used: physics; mathematics; Matlab; high-performance computation.I am designing and implementing next-generation algorithms for the metrology of semiconductor wafers using x-ray light, using Matlab for development work and C# for production code. These algorithms involve solving Maxwell's equations to determine the scattered light, the forward problem: given a semiconductor wafer with microscopic dimensions, how does light scatter from it? Given this capability to solve the forward problem, I use machine learning, maximum a posteriori estimation, and other methods to solve the inverse problem, because in optical metrology, we are fundamentally interested in solving the inverse problem: given the scattered light, what are the microscopic dimensions of the structures on the semiconductor wafer?