IEEE-SSCI 2018

2018 SYMPOSIUM SERIES ON COMPUTATIONAL INTELLIGENCE



18 - 21 NOVEMBER, 2018, BENGALURU, INDIA


IEEE Symposium on

Symposium on Neuromorphic Cognitive Computing

The 2018 IEEE Symposium on Neuromorphic Cognitive Computing (SNCC '17) will be held in Honolulu, Hawaii, USA from Nov. 27 to Dec 1, 2018. SNCC '17 will be a part of the IEEE Computational Intelligence Society (CIS) flagship conference, IEEE Symposium Series on Computational Intelligence 2018 (SSCI 2018). In recent years neuromorphic computing and neuromorphic engineering have become important emerging research areas. There has been rapid progress in various computational theories, learning algorithms, signal processing algorithm, circuit designs and implementations, which have shown appealing computational advantages over conventional approaches. Emulating the computational principles and architecture found in neural systems, neuromorphic cognitive computing studies sensory coding, synaptic computing, dendritic computing, unsupervised and supervised spike based learning rule, and high level of memory and cognition. The computational models and algorithms will be of fundamental importance to develop neuromorphic sensors, processors, and as well as sensory motor systems for robotic agents. The symposium will provide an important platform for the researchers across all related fields to exchange the ideas and report recent progress, and aims to bring new theoretical and technical advances in neuromorphic cognitive computing, neuromorphic engineering, and in turn to benefit highly demanded applications across machine learning, cognitive devices, neuromorphic circuits design and robotics, etc.

Topics

  •    Neuromorphic computing
  •    Cognitive computing
  •    Spiking neural networks (SNNs)
  •    Supervised and unsupervised learning
  •    STDP
  •    Neuromorphic visual and auditory processing
  •    Brain-inspired data representation
  •    Spike-based learning
  •    Neural coding
  •    Event based processing
  •    Brain inspired computing for sound, vision and speech
  •    Hardware implementation of SNNs
  •    Deep learning for SNNs
  •    FPGA or GPU accelerator for SNNs 
  •    Neuromorphic sensors and hardware systems
  •    Cognitive devices and robots
  •    SNN applications in machine learning and big data
  •    SNN applications in BCI
  •    SNN applications in Cyborg Intelligence

Symposium Co-Chairs


Huajin Tang
Sichuan University, China
Email: htang@scu.edu.cn


Jeff Krichmar
University of California at Irvine, USA
Email: jkrichma@uci.edu


Tiejun Huang
Peking University, China
Email: tjhuang@pku.edu.cn


Garrick Orchard
National University of Singapore, Singapore
Email: garrickorchard@nus.edu.sg

Program Committee

(To be announced)

Symposia