Research
Selected work on dynamical systems, stochastic modeling, and rare and extreme events.
Explicitly incorporating local directions of strongest finite-time growth into the surrogate provides mechanistic information that is difficult to infer from scarce rare-event examples.
NeurIPS'26 oral
Efficiently predicts generalized steady-state responses in nonlinear mechanical systems under aperiodic forcing, without long transient simulations.
Detects early drought stress in soybean plants non-intrusively through a change in their nonlinear vibration dynamics, captured by the evolution of spectral submanifolds (SSMs).