Optimization is concerned with the analysis and algorithmic aspects of maximizing or minimizing an objective function subject to constraints, often in complex problems in high dimension. Active research areas in ORFE include interior-point methods, the parametric simplex method, stochastic optimization, and convex analysis. Applications of interest span from portfolio optimization to engineering applications such as optimal control, optical design, and machine learning.

Research Area Faculty

Amir Ali Ahmadi

Research Interests: Optimization, dynamical systems, learning for dynamics and control, computational complexity. Applications of these disciplines to optimization problems in systems theory, portfolio management, machine learning, and robotics.

Alain Kornhauser

Research Interests: Autonomous Vehicles, SmartDrivingCars, the fundamental design of computer vision techniques for for the rapid classification and identification of the driving environment, analysis and classification of collision-free driving scenarios, quantification of accident risk and the investigation, formulation…

John Mulvey

Research Interests: Financial optimization models and associated algorithms, asset management strategies for global pension plans, (re)insurance companies, and other long-term investors, dynamic portfolio tactics for hedge funds, replicating performance of active managers

Bartolomeo Stellato
Assistant Professor

Research Interests: Data-driven computational tools for mathematical optimization, machine learning and optimal control. Real-time and embedded optimization. Dynamical systems and optimization-based control. Differentiable optimization. First-order methods for large scale optimization. Machine learning for optimization and…