About

Jacob M. Aguirre is an Operations Research Ph.D. student in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Prior to joining ISyE, he was a B.S./M.S. student in economics and mathematics.

Aguirre's research interests lie in the area of continuous optimization and complexity of algorithms. More specifically, he is interested in the theory, complexity analysis, and implementation of algorithms for solving large-scale linear programming (LP), convex quadratic programming (CQP), semidefinite programming (SDP), complementarity problems, convex programming, saddle-point problems, variational inequalities, and general nonlinear programming.  He is also interested in computational optimization and in developing numerical codes for solving large-scale optimization problems.

His current research includes optimization theory and methods for large-scale linear and conic programming with Renato D.C. Monteiro; classical operations research and logistics with Anton J. Kleywegt; and the iteration complexity of convex optimization algorithms and study of acceleration, non-Euclidean geometry, and lower complexity bounds with Dmitrii Ostrovskii.

Aguirre’s research has been supported by fellowships and awards through the National Science Foundation Graduate Research Fellowship Program, the U.S. Department of Energy, Oak Ridge National Laboratory, the GEM Ph.D. Fellowship program, The Coca-Cola Company, Ernst & Young, and the Georgia Institute of Technology. His honors include the Jessie and Ralph W. Pries Fellowship, Stewart Fellowships, and the Presidential Fellowship.