My research interests are in the area of continuous optimization and algorithmic complexity.

• (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 numerical codes for solving these large-scale optimization problems efficiently

Çaglar Çaglayan, Yunan Liu, Turgay Ayer, et al. Physician staffing in emergency rooms (ERs): Opening the black-box of ER care via a multi-class multi-stage network. (Under revision at Management Science.)

Renato D.C. Monteiro, Jacob M. Aguirre, Anton J. Kleywegt. A Low-Rank Augmented Lagrangian Method for Large-Scale Sparse Linear Programming Based on a Hybrid Approach. (Working paper)

Jacob M. Aguirre, Anton J. Kleywegt, Renato D.C. Monteiro. Efficient algorithms for Bicriteria Traffic Assignment (Working paper)

Jacob M. Aguirre, Anton J. Kleywegt, Renato D.C. Monteiro. Accelerated GPU methods for FOMs.

Xinchao Liu, Jacob M. Aguirre, Xiao Liu. Optimal Compressed Sensing Dynamic Mode Decomposition for In-Situ Large-scale Dataset.* (Under revisions)

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