Neuromorphic Computing

Lead Professor: Dr. Jennifer Hasler

"if you build it, you understand it. And if you understand it, you can build it" -- Carver Mead

Neuromorphic Systems: have systems based on neuroscience, to perform biological like tasks, including robotics, and thereby contribute to neuroscience understanding.

Neuromorphic computing looks at the connection between neurobiological and silicon systems to build networks of synapses, dendrites, and neurons that results in both competitive engineering applications and new questions to investigate the underlying neuroscience.

References :
[1] J. Hasler, "We could build an artificial brain right now," IEEE Spectrum , June 2017.
[2] J. Hasler, H. B. Marr, "Finding a Roadmap to achieve Large Neuromorphic Hardware Systems," Frontiers in Neuroscience, vol. 7, no. 118, September 2013. pp. 1-29. DOI=10.3389/fnins.2013.00118
[3] A. Natarajan and J. Hasler, “Hodgkin Huxley Neuron and FPA A Dynamics,” Transactions on Biological Circuits and Systems, Vol. 12, no. 4, August 2018. pp. 918-926.
[4]
[5] H. B. Marr and J. Hasler, "Compiling probabilistic, bio-inspired circuits on a field programmable analog array," Frontiers in Neuroscience, 2015. pp. 1-9.
[6] http://www.eetimes.com/document.asp?doc_id=1322022
[7] http://www.kurzweilai.net/neuromorphic-computing-roadmap-envisions-analog-path-to-simulating-human-brain
[8] http://www.extremetech.com/extreme/181096-researchers-create-a-roadmap-for-neuromorphic-brain-like-cpus
[9] http://phys.org/news/2014-04-neuromorphic-roadmap-envisions-analog-path.html