Anton Anders holds a master’s degree in Applied Mathematics and Programming. Prior to joining NVIDIA, he worked at Intel, first as a software developer at Intel MKL responsible for SparseBlas and Pardiso (direct sparse solver). Then he moved to Intel's MKL-DNN team and worked on developing highly optimized kernels (GEMM and Convolution) for current and future Intel architectures. At NVIDIA, Anton is covering several projects, including cuSolver, cuSparse, HPL, and cuDSS. His primary area of focus is optimizations for future architectures.