Research Focus

I work on scientific machine learning for dynamical systems mostly coming from Hamiltonian, quantum, and nonlinear wave settings. An emerging theme of my research is to combine mathematical analysis, numerical methods, and machine learning to produce models that respect invariants, symmetries, and physical structure. Most of my earlier work involves optimal control theory and nonlinear waves.

New and Active Projects (more info coming soon!)

• Reduced order models for coherent structures
• Learning integrability and integral transforms from symbolic data
• Intrinsic neural flows for long-time integration of PDEs

Latest

• Wei Zhu (@Georgia Tech) and I are organizing a minisymposium at SIAM NWCS '26 on structure preserving learning for nonlinear waves.
• We are gathering on Jan 30th @ ASU on the future of faculty development programs!
• I'm giving a talk on ROMs for nonlinear waves at Dynamics Days in January.
• Starting Fall of 2026, I will be a tenure track assistant professor at SoMSS, ASU!