Research interests
How can we make large networked systems easier to study without losing the properties that matter?
Optimal model order reduction
My current work studies reduced-order models of networked systems, particularly second-order models used in power system dynamics. I am interested in reducing approximation error while preserving network structure and essential dynamical properties.
- Structure-preserving projection and clustering-based reduction
- Semistable systems and preservation of synchronization behavior
- Optimization of reduced models using H2 error measures
Questions guiding my work
- Can we obtain an optimal reduced-order model while preserving the topological structure of the original network?
- How can we improve the scalability of optimization problems with Lyapunov equality constraints while preserving stability?
- How can traditional model reduction methods be adapted to modern power systems with heterogeneous dynamics, black-box equipment, and less distinct time-scale separation?
Dynamics of inverter-based power systems
My broader interests include grid-forming inverters, virtual oscillator control, droop control, and the dynamics of synchronization. I am interested in how changing generation technologies affect the modeling, analysis, and control of power systems.