David G. Clark

David G. Clark


Graduate Student in Neurobiology & Behavior @ Columbia University


I am a neuroscience PhD candidate at Columbia University, primarily advised by Larry Abbott. I work in the Center for Theoretical Neuroscience.

Using tools from physics and computer science, I aim to understand how biological and artificial neural circuits function and learn.


  • Theoretical neuroscience
  • Machine learning
  • Computational modeling


  • PhD in Neurobiology & Behavior

    Columbia University, 2019–Present

  • B.A. in Physics, Computer Science

    UC Berkeley, 2017


(2023). Theory of coupled neuronal-synaptic dynamics. arXiv.


(2022). Dimension of activity in random neural networks. arXiv.


(2021). Olfactory landmarks and path integration converge to form a cognitive spatial map. Neuron.

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(2021). Credit assignment through broadcasting a global error vector. NeurIPS 2021.

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(2019). Unsupervised discovery of temporal structure in noisy data with dynamical components analysis. NeurIPS 2019.

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