Neuromorphic Computing Resources

What do you need to know as background for neuromorphic research?

  • Machine learning concepts
    • What is a deep neural network?
    • How do methods like stochastic gradient descent work?
  • Spiking neural networks - how do they differ from DNNs?

Undergraduate students in this area have suggested the following resources as being helpful for these topics:

Suggested Background for Georgia Tech Undergrads

  • A background in data structures and machine learning concepts (CS 1332 and 4641)
  • Special topics courses like “Computation and the Brain” (CS8803-CAB) when offered
  • Courses from the neuroscience undergraduate track like “Principles in Neuroscience” (NEURO 2001) would likely also be helpful but may require more of a biomedical background.


  • How to build a brain by Chris Eliasmith - a book by one of the current leaders in neuromorphic computing research
  • Neuronal Dynamics - an online book by EPFL
  • Principles of Neural Science - well-regarded book that focuses on the neuroscience aspect of brain functions. Note this does not strictly talk about neuromorphic computing but it provides a good background as to how many neuromorphic systems are designed to mimic the brain.


Survey Papers

Other Resources