Alexey Voronin
I am a Senior Member of Technical Staff in the Center for Computing Research (CCR) at Sandia National Laboratories. I develop nonlinear and linear solvers and preconditioners for optimal control of Maxwell’s equations. In scientific machine learning, I use classical methods such as spectral analysis and domain decomposition to make neural network training faster, cheaper, and more accurate.
I earned my PhD in Computer Science from the University of Illinois at Urbana-Champaign. Before that, I spent three years as a software engineer at Lawrence Livermore National Laboratory, working on multiphysics simulation codes for GPUs and modern HPC architectures.
The best way to keep up with my work is through Google Scholar and GitHub.
selected publications
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On the convergence behavior of preconditioned gradient descent toward the rich learning regimeIn International Conference on Learning Representations , 2026