My research interests are in the area of continuous optimization and algorithmic complexity. I am especially interested in the intersection of convex algebraic geometry and Semidefinite Programming.

• (Major) Theory and complexity analysis: Development of efficient algorithms for large-scale linear programming, convex quadratic programming, semidefinite programming, variational inequalities, and nonlinear convex programming.
• (Minor) Computational optimization: Developing fast numerical codes for GPU-accelerated first-order solvers for large-scale optimization.

Jacob M. Aguirre, Renato D.C. Monteiro, Anton J. Kleywegt. Hybrid Approaches for Large-Scale Linear Programs (Working paper)

Jacob M. Aguirre, Anton J. Kleywegt, Renato D.C. Monteiro. An Efficient Method for the Bicriterion Traffic Assignment Problem. In submission to Operations Research.

Jacob M. Aguirre, Renato D.C. Monteiro, Anton J. Kleywegt. Iteration Complexity of an Accelerated Smoothing Gradient Method. In submission to Mathematics of Operations Research.

Jacob M. Aguirre and Renato D.C. Monteiro. A New Memory-efficient method for Sparse Plus Low Rank Semidefinite Programming

Jacob M. Aguirre, Renato D.C. Monteiro, Arnesh Sujanani. cuHALLaR-C: A strengthened implementation of cuHALLaR for Large-Scale Semidefinite Programming by C language

Jacob M. Aguirre, Diego Cifuentes, Vincent Guigues, Renato D.C. Monteiro, Victor Hugo Nascimento, Arnesh Sujanani. cuHALLaR: A GPU Accelerated Low-Rank Augmented Lagrangian Method for Large-Scale Semidefinite Programming. Preprint here. In submission to Mathematical Programming Computation.

Jacob M. Aguirre, Diego Cifuentes, Vincent Guigues, Renato D.C. Monteiro, Victor Hugo Nascimento, Arnesh Sujanani. A User Manual for cuHALLaR: A GPU Accelerated Low-Rank Semidefinite Programming Solver. Preprint here.

Jacob Aguirre, Shrey Patel, Ruirui Ma. A Review of High Dimensional Nonlinear Dimension Reduction Methods Undergrad course paper