Hi, I’m a postdoctoral researcher in Applied Mathematics and Computational Science at the University of Pennsylvania.
Hi, I’m a postdoctoral researcher in Applied Mathematics and Computational Science at the University of Pennsylvania.
I’m interested in mathematical problems inspired by natural phenomena, particularly those that lie at the intersection of probability, dynamical systems, and partial differential equations. Much of my work involves analyzing and simulating spatially extended stochastic systems that support wave-like behavior.
Stochastically Forced Brain Waves
Sharp Pulses in Stochastic FitzHugh-Nagumo Model used in Neuroscience
Isochronal Reduction
I applied a dimension-reduction technique for stochastic ODEs to a stochastic PDE to quantify how noise affects wave speed.
In the stochastic FitzHugh–Nagumo equation (left), noise introduces not only a mean-zero wobble in the propagation speed but also a systematic drift—positive or negative depending on the noise’s correlation structure.
Using singular-perturbation theory, I derived a kinematic model and applied the Isochronal Phase Reduction method. This formulation allows computation of the average noise-induced drift completely deterministically, without sampling random realizations of the wave. The approach greatly improves efficiency when estimating whether stochastic fluctuations make the wave travel faster or slower than in the noise-free case.
Ion Channel Dynamics in Membrane Voltage Propagation
The blue shows the voltage potential over the length of an axon. The orange shows whether the ion channel at that location is open (1) or closed (0).
Stochastic Ion Channels
Ion channels embedded in a cell membrane (such as in an axon) open and close in response to the local voltage potential, but their behavior is inherently stochastic. The collective, averaged activity of many neighboring channels can nevertheless produce the coherent propagation of an action potential, as shown in the simulated toy model on the left. In the figure, we simulate the upstroke of an action potential using a hybrid stochastic–deterministic system.
This work focuses on developing, simulating, and homogenizing such models to understand how microscopic channel variability shapes macroscopic voltage propagation.
Waves in a Random-Mass-Lattice
Waves in FPUT (Non-linear Lattice: ... Mass-Spring-Mass-Spring-Mass- ...)
Sound waves with long wavelengths can more easily penetrate walls or other barriers. In a similar way, a compression wave with a long wavelength traveling through a mass–spring lattice can overcome both the discreteness of the lattice and microscopic heterogeneities in its material properties. If the springs obey Hooke’s law, dispersion eventually causes the wave to vanish; however, if the springs are nonlinear, certain waves can propagate essentially undistorted for much longer times and distances.
My research focuses on the stochastic effects—and sometimes the surprising lack of them—on such nonlinear waves as they travel through heterogeneous lattices.
Papers and Pre-prints:
Using random walks to establish wavelike behavior in a linear FPUT system with random coefficients
Macroscopic wave propagation for 2D lattice with random masses
Approximation of (some) random FPUT lattices by KdV equations
Radiating Solitary Waves in an FPUT Lattice with Random Coefficients