Felipe Atenas
PhD in Applied Mathematics, University of Campinas, Brazil (2023)
Master of Science in Engineering, Applied Mathematics, Universidad de Chile (2019)
BSc in Engineering, Applied Mathematics, Universidad de Chile (2019)
My work focuses on optimisation theory and algorithms with applications in machine learning and operations research. I design and analyse decomposition methods for structured optimisation problems, namely, methods that exploit favourable structures by breaking large-scale models into smaller, more tractable pieces, and leverage on the underlying mathematical properties to recover proper, fitting solutions. I draw tools from nonlinear programming, variational analysis, convex optimisation, and stochastic programming.