Operations Research

Jacob M. Aguirre

Continuous optimization and large-scale algorithms for linear, conic, and nonlinear programs.

Georgia Tech College of Engineering

H. Milton Stewart School of Industrial and Systems Engineering

PhD candidate in Operations Research at Georgia Tech ISyE.

CV Research Software

I am advised by Professors Anton J. Kleywegt, Renato D.C. Monteiro, and Dmitrii M. Ostrovskii, and I work closely with Arkadi Nemirovski on theory, complexity analysis, and scalable optimization methods.

Research Group

Advisors, collaborators, and current submissions

Advisors and collaborators

Who I work with

I am advised by Anton J. Kleywegt, Renato D.C. Monteiro, and Dmitrii M. Ostrovskii at Georgia Tech ISyE. My recent work also involves collaborations with Arkadi Nemirovski, Diego Cifuentes, Vincent Guigues, Victor Hugo Nascimento, and Arnesh Sujanani.

Current submissions

Where recent papers are under review

cuHALLaR: submitted to Mathematical Programming Computation
Bicriterion traffic assignment: submitted to Operations Research
Accelerated smoothing gradient method: submitted to Mathematics of Operations Research
Hybrid approaches for large-scale linear programs: current working paper with Renato D.C. Monteiro and Anton J. Kleywegt

Research Themes

What I work on

Theory and complexity

Sharp guarantees for continuous optimization

I study the design and complexity of algorithms for linear programming, convex quadratic programming, semidefinite programming, complementarity problems, variational inequalities, and nonlinear convex programming.

Computation and scale

Methods that survive contact with large instances

A parallel thread of my work focuses on numerical methods and software for large-scale optimization, including low-rank structure, first-order techniques, and GPU-accelerated solvers.