Alexis Montoison

Alexis Montoison is a postdoctoral researcher in the Mathematics and Computer Science division at Argonne National Laboratory. He focuses on developing high-performance algorithms for sparse linear algebra, continuous optimization, and automatic differentiation, with an emphasis on multi-architecture compatibility across CPUs and GPUs. He received his Ph.D. in applied mathematics from Polytechnique Montréal under the supervision of Dominique Orban where he was awarded GERAD's Best Thesis Award for his work, "Krylov Methods for Linear Algebra and Polymorphic Implementation." Alexis has developed several novel iterative solvers and techniques for large-scale linear systems, including MinAres, an iterative solver for symmetric linear systems. He is the principal developer of both Krylov.jl and libHSL, a collection of widely used libraries of sparse matrix algorithms. His academic achievements have been recognized through multiple honors, including travel awards from SIAM and scholarships from the Arbour Foundation, FRQNT, and IVADO, underscoring his dedication to advancing both theoretical and numerical approaches in numerical linear algebra and optimization methods.