activity
20112026
most citedEpidemic extinction and control in heterogeneous networks

79 citations · 354 across the 29 of their papers we have counts for

collaborators

30 papers

nlin.AO2026

Redirecting counter-moving swarms through collision

Jason Hindes, Chinthan B. Prasad, Loy McGuire +1

Multi-swarm systems, where two or more swarms of mobile agents occupy the same region of space with different parameters and goals, occur in a variety of biological, engineering, a…

nlin.AO2026

Time delay in the 1d swarmalator model

K. P. O'Keeffe, Jason Hindes

We study the 1d swarmalator model augmented with time delayed coupling. Along with the familiar sync, async, and phase wave states, we find a family of unsteady states where the or…

nlin.AO2025

Target-density formation in swarms with stochastic sensing and dynamics

Jason Hindes, George Stantchev, Klimka Szwaykowska Kasraie +1

An important goal for swarming research is to create methods for predicting, controlling and designing swarms, which produce collective dynamics that solve a problem through emerge…

stat.ME2025

Multi-rank Subspace Change-point Detection with Application in Monitoring Robotic Swarms

Jonghyeok Lee, Yao Xie, Youngser Park +3

We study real-time detection of low-rank changes in the covariance structure of high-dimensional streaming data, motivated by robotic swarm monitoring. Building on the spiked covar…

physics.optics2024

Noise-induced peak intensity fluctuations in class B laser systems

Jason Hindes, Ira B. Schwartz

Random perturbations and noise can excite instabilities in population systems that result in large fluctuations. An interesting example involves class B lasers, where the dynamics…

q-bio.PE2023

Outbreak-size distributions under fluctuating rates

Jason Hindes, Luis Mier-y-Teran-Romero, Ira B. Schwartz +1

We study the effect of noisy infection (contact) and recovery rates on the distribution of outbreak sizes in the stochastic SIR model. The rates are modeled as Ornstein-Uhlenbeck p…