Eve Armstrong is a theorist in physics who is interested in modeling nonlinear phenomena in neuroscience—particularly phenomena related to acoustic signal processing. She also conducts research in astrophysics.

Armstrong received her B.A. in astrophysics from Columbia University in 2002 and her Ph.D. in physics from the University of California, San Diego (UCSD) in 2013, with a dissertation on observational astrophysics. She then worked as a postdoctoral scholar in the physics group of Henry Abarbanel at UCSD, modeling neuronal networks associated with vocalization and audition in songbirds, and using methods of data assimilation to test and complete those models.

In a second postdoctoral fellowship at the Computational Neuroscience Initiative (CNI) at the University of Pennsylvania (UPenn), Armstrong expanded these modeling efforts to begin developing a geometrical approach to analyzing natural acoustic signals. With all neuroscience-related projects, she works closely with experimentalists specializing in birdsong and animal behavior.

In addition to her scholarship, Armstrong has a keen interest in public engagement with science. With a background in theatre, she co-founded Reality Aside Theatre, a 501(c)(3) (tax-exempt) company incorporated in New York in 2007, and experimented with educational science sketch comedy for the general public. In the classroom, she experiments with artistic methods of exploring scientific concepts.

Recent Projects/Research

  • A geometric dynamical systems approach to analyzing the information content of birdsong. Collaborators: Marc Schmidt: Laboratory of Avian Neuro-ethology, UPenn.
  • Understanding song learning—and unlearning—in juvenile birds. Collaborators: Julia Hyland Bruno (Columbia University), Ofer Tchernichovski (Hunter College, CUNY), Tiberiu Tesileanu (Flatiron Institute).
  • Optimization approaches to calculating neutrino flavor evolution. Collaborators: George Fuller (UCSD), Baha Balantekin and Amol Patwardhan (University of Wisconsin, Madison), Chad Kishimoto (University of San Diego), Shashank Shalgar (University of Copenhagen, Denmark).


  • Armstrong, E. An optimization method for estimating functional connectivity and electrophysiology within a biological neuronal network. (In revision: PLOS One); arXiv preprint https://arxiv.org/abs/1711.03834, 2018
  • Armstrong, E., Patwardhan, A.V., Johns, L., Kishimoto, C.T., Abarbanel, H.D.I., Fuller, G.M. A Path-integral-based Approach to Neutrino Flavor Evolution. Physical Review D 96(8): 083008, 2017
  • Abarbanel, H.D.I., Shirman, S., Breen, D., Kadakia, N., Rey, D., Armstrong, E., Margoliash, D. A Unifying View of Synchronization for Data Assimilation in Complex Nonlinear Networks. Chaos: An Interdisciplinary Journal of Nonlinear Science, 27(12): 126802, 2017
  • Abarbanel, H.D.I., Shirman, S., Armstrong, E., Dean D., Extracellular Potentials as Data Assimilation Measurement Functions for the Dynamics in Networks of Neurons. (In preparation)
  • Armstrong, E., Abarbanel, H.D.I. Model of the songbird nucleus HVC as a network of central pattern generators, J. Neurophysiol. 116(5): 2405-2419, 2016

Courses Taught at New York Tech

  • Phys 180: General Physics II