Research Interests

• Model Order Reduction of Linear and Nonlinear Systems
  Developing efficient algorithms for reducing complex dynamical systems while preserving essential characteristics for analysis and control.
• Switched Systems
  Studying systems that switch between different modes of operation, with a focus on stability, control, and model reduction.
• Optimization
  Exploring advanced optimization techniques for solving engineering and mathematical problems, including large-scale and real-world applications.
• Machine Learning
  Applying machine learning methods to system identification, prediction, and control, with emphasis on data-driven modeling and hybrid approaches.
• Differential-Algebraic Equations
  Investigating the theory and numerical solution of DAEs, particularly as they relate to control, simulation, and reduction of complex systems.