Call for Papers

With the looming end of the “Moore’s Law” era, there is an emerging challenge to “proactively interpret and learn from data, solve unfamiliar problems using what it has learned, and operate with the energy efficiency of the human brain."

We believe neuromorphic computing will play a major role in this challenge, and has the potential to transform the way we use computers through new materials, new brain-inspired chips, greater understanding of neuroscience, and breakthroughs in machine understanding/intelligence. Neuromorphic computing systems have the potential to mimic the functionality of neural systems in the brain, which we believe will lead to more powerful and efficient computing paradigms. These new systems have the potential to help scientists pioneer new scientific discoveries, or to help intelligently analyze sensor data for improved cyber security or energy management.

The goal of this workshop is to bring together leading researchers in neuromorphic computing to present new research, develop new collaborations, and provide a forum to publish work in this area. Our focus will be on architectures, models, and applications of neuromorphic systems, resulting from a very successful workshop last year.

Research papers are requested for topics on Neuromorphic Computing. There are three focus areas, though papers outside the scope of these areas but within Neuromorphic Computing will be considered:

1. Architectures, Models, and Emulation: including network, neuron, and synapse models, emerging hardware implementations, and efficient simulation techniques for large-scale networks
2. Machine intelligence algorithms for programming or training neuromorphic devices: including supervised and unsupervised learning methods and biologically-inspired algorithms.
3. Applications for and use-cases of neuromorphic systems, including those where neuromorphic systems have the potential to outperform state-of-the-art techniques. This topic area also includes supporting software systems that enable application development for neuromorphic systems and suggestions for benchmark tasks for neuromorphic computing.

We are accepting submissions in the following forms:

1. Full papers (6-8 pages), which will be considered for full (20 minute) presentations. A 1-2 page extended abstract (not including references) is due prior to the full paper submission.
2. Extended abstracts (1-2 pages not including references) for lightning talks and/or poster presentations.

Select papers will be invited to submit extended versions for a special issue of the ACM Journal of Emerging Technologies (JETC).